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Question: <p>My understanding of boosting is just training models sequentially and learning from its previous mistakes.</p>
<p>Can boosting algorithms be built with bunch of logistic regression? or logistic regression + decision trees?</p>
<p>If yes, I would like to know some papers or books that covers this topic in-d... | https://datascience.stackexchange.com/questions/101891/boosting-algorithms-only-built-with-decision-trees-why |
Question: <p>I'm trying to fully understand the gradient boosting (GB) method. I've read some wiki pages and papers about it, but it would really help me to see a full simple example carried out step-by-step. Can anyone provide one for me, or give me a link to such an example? Straightforward source code without tricky... | https://datascience.stackexchange.com/questions/9134/gradient-boosting-algorithm-example |
Question: <p>In the very early papers on gradient boosting, the ensemble would include a constant and a sum of base learners i.e.</p>
<p><span class="math-container">$F(X) = a_0 + \sum\limits_{i} a_i f_i(X)$</span></p>
<p>The constant is fitted first (i.e. if the loss is squared error, the <span class="math-container... | https://datascience.stackexchange.com/questions/56041/gradient-boosting-where-did-the-constant-go |
Question: <p>I am having a look at this <a href="https://github.com/lesteve/euroscipy-2019-scikit-learn-tutorial/blob/master/notebooks/02_basic_preprocessing.ipynb" rel="noreferrer">material</a> and I have found the following statement:</p>
<blockquote>
<p>For this class of models [Gradient Boosting Machine algorithms]... | https://datascience.stackexchange.com/questions/78092/on-gradient-boosting-and-types-of-encodings |
Question: <p>In Random Forest each tree is built selecting a sample with replacement (bootstrap). And I assumed that Gradient Boosting's trees were selected with the same sampling technique. (@BenReiniger corrected me). <a href="https://catboost.ai/docs/concepts/algorithm-main-stages_bootstrap-options.html" rel="noref... | https://datascience.stackexchange.com/questions/67674/why-gradient-boosting-uses-sampling-without-replacement |
Question: <p>I'm trying to solve <a href="https://www.kaggle.com/c/quora-question-pairs" rel="nofollow noreferrer">Quora Question Pairs</a> with model stacking.</p>
<p>My first layers are:</p>
<ul>
<li>CNN trained to predict the same target as whole model should</li>
<li>"Magic features" like question frequen... | https://datascience.stackexchange.com/questions/31026/averaging-cnn-perform-worse-than-boosting |
Question: <p>looking through the mathematics of gradient boosting on the relevant <a href="https://en.wikipedia.org/wiki/Gradient_boosting" rel="nofollow noreferrer">wikipedia page</a>, intuitively what is the purpose of the multiplier <span class="math-container">$\gamma_i$</span>?</p>
<p><a href="https://i.sstatic.n... | https://datascience.stackexchange.com/questions/60965/purpose-of-gamma-multiplier-in-gradient-boosting |
Question: <p>I just stepped in machine learning competitions and it looks like most of the mid-sized dataset competitions are won by Gradient boosting based models. However I came accross case where <a href="https://lightgbm.readthedocs.io/en/latest/" rel="nofollow noreferrer">LightGBM</a>,<a href="https://catboost.ai/... | https://datascience.stackexchange.com/questions/92717/chossing-between-gradient-boosting-algorithms |
Question: <p>Boosting is a sequential technique in which, the first algorithm is trained on the entire dataset and the subsequent algorithms are built by fitting the residuals of the first algorithm, thus giving higher weight to those observations that were poorly predicted by the previous model. Examples are adaboost ... | https://datascience.stackexchange.com/questions/17147/how-to-do-boosting-in-model-ensembling |
Question: <p>Stacking can be achieved with heterogeneous algorithms such as RF, SVM and KNN. However, can such heterogeneously be achieved in Bagging or Boosting? For example, in Boosting, instead of using RF in all the iterations, could we use different algorithms?</p>
Answer: <p>The short answer is <strong>yes</stro... | https://datascience.stackexchange.com/questions/92847/can-boosting-and-bagging-be-applied-to-heterogeneous-algorithms |
Question: <p>I understand the main principle of bagging and boosting for classification and regression trees. My doubts are about the optimization of the hyperparameters, especially the depth of the trees</p>
<p><strong>First question</strong>: why we are supposed to use weak learners for boosting (high bias) whereas... | https://datascience.stackexchange.com/questions/61771/bagging-vs-boosting-bias-vs-variance-depth-of-trees |
Question: <p>I struggle to grasp the role of gradient based optimization in boosting ensembles. As far as I understand boosting means combining a bunch of estimators (of the same types, usually decision trees) sequentially -- each subsequent one is learning from the errors of the previous ones (by upweighting the miscl... | https://datascience.stackexchange.com/questions/86492/how-to-interpret-gradient-descent-in-boosting-ensembles |
Question: <p>While it is obviously clear that features can be ranked on basis of importance and many machine learning books give examples of random forests on how to do so, its not very clear on which occasions one should do so.</p>
<p>In particular, for boosting methods, is there any reason why one should do feature ... | https://datascience.stackexchange.com/questions/11081/importance-of-feature-selection-for-boosting-methods |
Question: <p>I am trying to tune a Regression gradient boosting model where my target variable is zero inflated (80% zero) and the rest of the values are distributed as positive and negative values (not necessary symmetrically). What are good practices when training a model like this? </p>
<p>Any specific issues which... | https://datascience.stackexchange.com/questions/69949/gradient-boosting-regression-with-zero-inflated-outcome |
Question: <p>If we consider two conditions:</p>
<ol>
<li>Number of data is huge </li>
<li>Number of data is low</li>
</ol>
<p>For what condition does boosting or bagging overfit more compared to the other one?</p>
Answer: <p>I read your question as: 'Is boosting more vulnerable to overfitting than bagging?'</p>
<p>... | https://datascience.stackexchange.com/questions/28299/when-does-boosting-overfit-more-than-bagging |
Question: <p>I have read in some papers that the subset of features chosen for a boosting tree algorithm will make a big difference on the performance<br />so I've been trying RFE, Boruta, Clustering variables, correlation, WOE & IV and Chi-square</p>
<p>Let's say I have a classification problem with over 40 variab... | https://datascience.stackexchange.com/questions/84624/feature-selection-before-modeling-with-boosting-trees |
Question: <p>I wish to train some data using the <a href="https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html#sklearn-ensemble-gradientboostingregressor" rel="nofollow noreferrer">the Gradient Boosting Regressor of Scikit-Learn</a>.</p>
<p>My questions are:</p>
<p>1) Is t... | https://datascience.stackexchange.com/questions/45371/does-gradient-boosting-detect-non-linear-relationships |
Question: <p>I have a binary classification task where all of my features are boolean (0 or 1). I have been considering two possible supervised learning algorithms:</p>
<ul>
<li>Logistic regression</li>
<li>Gradient boosting with <a href="https://en.wikipedia.org/wiki/Decision_stump" rel="nofollow noreferrer">decisio... | https://datascience.stackexchange.com/questions/18081/gradient-boosting-vs-logistic-regression-for-boolean-features |
Question: <p>I am checking out XGBoost documentation and it's stated that XGBoost is an optimized <strong>distributed</strong> gradient boosting library. </p>
<p>What is meant by distributed?</p>
<p>Have a nice day</p>
Answer: <p>It means that it can be run on a <a href="https://en.wikipedia.org/wiki/Distributed_com... | https://datascience.stackexchange.com/questions/41266/what-is-meant-by-distributed-for-a-gradient-boosting-library |
Question: <p>For implementation I am following the <a href="https://www.mathworks.com/matlabcentral/fileexchange/63162-adaboost" rel="nofollow noreferrer">Matlab code for AdaBoost</a>. Based on my understanding, AdaBoost uses weak classifiers known as base classifiers and creates several instances of it. For example, a... | https://datascience.stackexchange.com/questions/33392/is-ensemble-learning-using-different-classifier-combination-another-name-for-boo |
Question: <p>In the category of Gradient Boosting, I find some terms confusing.</p>
<p>I'm aware that XGBoost includes some optimization in comparison to conventional Gradient Boosting.</p>
<ul>
<li><p>But are <strong>Gradient Boosting Machines (GBM)</strong> and <strong>GBDT</strong> the same
thing? Are they just diff... | https://datascience.stackexchange.com/questions/81963/are-gradient-boosting-machines-gbm-and-gbdt-exactly-the-same-thing |
Question: <p>What kind of problem, circumstances and data makes it more suitable to apply boosting instead of bagging methods?</p>
Answer: <p>Bagging and boosting are two methods of implementing ensemble models.</p>
<p>Bagging: each model is given the same inputs as every other and they all produce a model</p>
<p>Bo... | https://datascience.stackexchange.com/questions/58269/how-does-one-decide-when-to-use-boosting-over-bagging-algorithm |
Question: <p>I read a lot about random forest and gradient boosting, but I do not know how these two algorithms really work.</p>
<p>For example, see the simple picture about basketball (picture 1) from <a href="https://www.r-bloggers.com/how-random-forests-improve-simple-regression-trees/" rel="nofollow noreferrer">th... | https://datascience.stackexchange.com/questions/28672/regression-how-random-forest-and-gradient-boosting-really-works |
Question: <p>In boosting process we get a better accuracy for training data, but there is a lot of chance to over fit. For bagging ensemble method over fitting chance is lower than boosting.
Why we use boosting and for what condition ??</p>
Answer: <p>Bagging (and features sampling) aim to reduce variance by providin... | https://datascience.stackexchange.com/questions/28173/for-what-condition-boosting-work-better-than-bagging-in-ensemble-learner |
Question: <p>Theoretical Noob question -</p>
<p>Can we use boosting methods to effectively forecast the future after being trained on a non-stationary time series? Or do you train/fit on the residual of the training set and then add seasonality/trend components while forecasting?</p>
<p>Thanks in advance.</p>
Answer: ... | https://datascience.stackexchange.com/questions/88441/forecasting-using-boosting-methods-on-non-stationary-time-series-data |
Question: <p>I am working on an e-commerce data where the goal is to predict how will the user rate a movie from 1 to 5. We have a bunch of data from users but also from products. Some users have previously rated more than 10 (even 100s) and some less. Something like the following.</p>
<p><a href="https://i.sstatic.net... | https://datascience.stackexchange.com/questions/94300/building-a-boosting-model-for-repeated-measurments |
Question: <p>What are the best strategy to train and save a gradient boosting algorithm, e.g. LightGBM or XGboost or Catboost in Python but load the model in GoLang and make prediction with Golang ?</p>
Answer: <p>There's actually a few libraries that handle the inference part well. <a href="https://github.com/dmitry... | https://datascience.stackexchange.com/questions/82636/training-gradient-boosting-algorithm-in-python-testing-in-golang |
Question: <p>I am learning <a href="https://youtu.be/t-XJ6AfqULg?t=583" rel="nofollow noreferrer">boosting</a>, the machine learning ensemble meta-algorithm. The professor is grouping 3 weak classifiers into an ensemble and said that before this <a href="https://youtu.be/t-XJ6AfqULg?t=584" rel="nofollow noreferrer">tim... | https://datascience.stackexchange.com/questions/51646/what-does-exaggeration-mean-in-the-context-of-boosting |
Question: <p>I am tuning a regression gradient boosting-based model to determine the appropriate hyperparameters using 4-folds cross validation. More specifically, I am using XGBoost and lightGBM for the models and Bayesian optimization algorithm for the hyperparameters search (hyperopt)</p>
<p>One of the hyperparamete... | https://datascience.stackexchange.com/questions/68635/small-number-of-estimators-in-gradient-boosting |
Question: <p>I am training a gradient boosting classifier on an imbalanced data but the model is not performing very well. These are the things I have done to improve the model's performance.</p>
<ol>
<li>Balanced the data with SMOTE</li>
<li>Added more variables</li>
<li>combined features</li>
<li>polynomial feature t... | https://datascience.stackexchange.com/questions/126473/improving-the-performance-of-gradient-boosting-classifier |
Question: <p>For some machine learning methods it is recommended to use feature normalization to use features that are on the same scale, especially for distance based methods like k-means or when using regularization. However, in my experience, boosting tree regression works less well when I use normalized features, f... | https://datascience.stackexchange.com/questions/16225/would-you-recommend-feature-normalization-when-using-boosting-trees |
Question: <p>I have been reading about gradient boosting trees (GBT) in some machine learning books and papers, but the references seem to only describe the training algorithms of GBT, but they do not describe the formula of a GBT model. So, I am not sure how a GBT model predict a new instance.</p>
<p>What is the formu... | https://datascience.stackexchange.com/questions/108545/what-is-the-formula-of-gradient-boosting-trees-model |
Question: <p>I am building another XGBoost model and I'm really trying not to overfit the data. I split my data into train and test set and fit the model with early stopping based on the test-set error which results in the following loss plot:</p>
<p><a href="https://i.sstatic.net/dLIDt.png" rel="nofollow noreferrer"><... | https://datascience.stackexchange.com/questions/80530/does-gradient-boosting-algorithm-error-always-decrease-faster-and-lower-on-train |
Question: <p>What I understood is that even gradient boosting for binary classification uses regression trees. The first value we calculate is constant = log(odds).
For the rest of the trees, we try to fit regression trees on the residuals.
But how do we fit the trees? Or how is the best splitting feature calculated? I... | https://datascience.stackexchange.com/questions/102160/how-are-regression-trees-fitted-in-gradient-boosting-for-classification |
Question: <p>I have a big data problem with a large dataset (take for example 50 million rows and 200 columns). The dataset consists of about 100 numerical columns and 100 categorical columns and a response column that represents a binary class problem. The cardinality of each of the categorical columns is less than 50... | https://datascience.stackexchange.com/questions/2504/deep-learning-vs-gradient-boosting-when-to-use-what |
Question: <p>I've searched everywhere and still couldn't figure this one out.
<a href="https://365datascience.com/career-advice/job-interview-tips/machine-learning-interview-questions-and-answers/#2:%7E:text=8.%20What%20are%20the%20bias%20and%20variance%20in%20a%20machine%20learning%20model%20and%20explain%20the%20bias... | https://datascience.stackexchange.com/questions/115320/why-is-gradient-boosting-better-than-random-forest-for-unbalanced-data |
Question: <p>I have asked this question <a href="https://stats.stackexchange.com/questions/550948/feature-importance-by-random-forest-and-boosting-tree-when-two-features-are-heav">here</a> but seems no one is interested in it.</p>
<p>Here is my understanding, <code>pls correct me if there is any misunderstanding:</code... | https://datascience.stackexchange.com/questions/103898/feature-importance-by-random-forest-and-boosting-tree-when-two-features-are-heav |
Question: <p>In our book there is boosting algorithm using column generation method (Dantzig-Wolfe decomposition) to solve the dual problem.<br />
So lets say we have want to solve the following primal linear problem based on hinge loss:<br />
<span class="math-container">$$\min_{w,\xi} \Sigma_{m=1}^Mw_m + C\Sigma_{i=1... | https://datascience.stackexchange.com/questions/80584/solving-the-dual-problem-of-boosting-using-column-generation |
Question: <p>I'm trying to get a better grasp of model interpretability using many different kinds of models for a binary classification problem.</p>
<p><em>Quick note: By interpretability in this case, what I mean is understanding which features have the largest effect on the target. (Not necessarily understanding ho... | https://datascience.stackexchange.com/questions/67843/interpreting-adaboost-model-results |
Question: <p>Christoph Molnar, in his book <a href="https://christophm.github.io/interpretable-ml-book/" rel="nofollow noreferrer">Interpretable Machine Learning</a>, writes that</p>
<blockquote>
<p>Human level evaluation (simple task) is a simplified application level
evaluation. The difference is that these experimen... | https://datascience.stackexchange.com/questions/92227/reliability-of-human-level-evaluation-of-the-interpretability-quality-of-a-model |
Question: <p>I know it depends on the data and question asked but imagine a scenario that for a given dataset you could either go for a fairly complex nonlinear model (hard to interpret though) giving you a better prediction power perhaps because the model may see the nonlinearities present in the data, or have a simpl... | https://datascience.stackexchange.com/questions/26511/how-would-you-describe-the-trade-off-between-model-interpretability-and-model-pr |
Question: <p><a href="https://datascience.stackexchange.com/questions/70164/what-is-the-difference-between-explainable-and-interpretable-machine-learning">This post</a> attempts to explain the difference between explainability and interpretability of ML models. However, the explanation is somewhat unclear. Can somebody... | https://datascience.stackexchange.com/questions/99808/an-example-of-explainable-but-not-interpretable-ml-model |
Question: <p>When reading the Tensorflow tutorial for <em>Word Embeddings</em>, I found two notes that confuse me:</p>
<blockquote>
<p>Note: Experimentally, you may be able to produce more interpretable embeddings by using a simpler model. Try deleting the Dense(16) layer, retraining the model, and visualizing the embe... | https://datascience.stackexchange.com/questions/118804/understand-the-interpretability-of-word-embeddings |
Question: <p>I am doing some work with R and after obtaining the confusion matrix I have obtained the following metrics corresponding to a logistic regression:</p>
<pre><code>Accuracy : 0.7763
95% CI : (0.6662, 0.864)
No Information Rate : 0.5395
P-Value [Acc > NIR] : 1.629... | https://datascience.stackexchange.com/questions/109916/how-are-the-confidence-intervals-of-a-model-interpreted |
Question: <p>If I trained a model (say logistic regression) on train, test and validation. During interpretation which dataset (test or validation) should I base on for interpretation? If test and validation shows some difference in performance (say 10% where test is higher than validation in terms of accuracy) does it... | https://datascience.stackexchange.com/questions/114248/interpreting-model |
Question: <p>Is it OK to use Binary Encoding in a dataset containing categorical columns with very high cardinalities?
Some facts about my dataset:</p>
<ul>
<li>My dataset has ~170,000 rows</li>
<li>One of the categoric variables has 1,700 unique values.</li>
<li>Another one has 3,000 unique values.</li>
<li>Note that ... | https://datascience.stackexchange.com/questions/39094/binary-encoding-in-decision-tree-random-forest-algorithms |
Question: <p>I am using the text of comments on a forum to predict how many upvotes it will get. I want to be able to say, "Reviews with X, Y, Z words are more upvoted". So to do this, I want to use text features in a regression. In particular,</p>
<p>What model should I use to maximize interpretability of coefficient... | https://datascience.stackexchange.com/questions/55019/what-model-is-recommended-i-am-using-text-features-in-a-regression-and-want-to |
Question: <p>I have time series GDP growth rate data that I use as my Y and other X variables that I put into neural networks to make predictions. The two questions that I have are:</p>
<ol>
<li><p>When I decompose my GDP_growth variable I get a detrended variable that I model and make predictions of. If I have train a... | https://datascience.stackexchange.com/questions/128130/decomposition-and-scaling-and-their-effect-on-interpretability |
Question: <p><strong>What I am doing:</strong></p>
<p>I am predicting product ratings using boosted trees (XGBoost) with a dataset in this format:</p>
<p><a href="https://i.sstatic.net/UssVN.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/UssVN.png" alt="enter image description here" /></a></p>
<p><stron... | https://datascience.stackexchange.com/questions/60466/how-to-restructure-my-dataset-for-interpretability-without-losing-performance |
Question: <p><a href="https://i.sstatic.net/GbG2Y.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/GbG2Y.png" alt="enter image description here" /></a></p>
<p>Hi everyone,</p>
<p>the above graph is produced by a BiLSTM model i just trained and tested. I can't seem to interpret it while it is very differen... | https://datascience.stackexchange.com/questions/84394/how-to-interpret-this-plot-of-model-loss-from-a-bilstm-model |
Question: <p>I am trying to interpret the p-values for model selection. Here is a sample code taken from a book (<a href="http://www-bcf.usc.edu/~gareth/ISL/" rel="nofollow noreferrer">An Intro. to stat. Learning, page 290, by Gareth James et al.</a>)</p>
<p><a href="https://i.sstatic.net/Qo8f7.png" rel="nofollow nore... | https://datascience.stackexchange.com/questions/11248/model-selection-by-interpreting-p-value-of-anova-function |
Question: <p>I tried building a keras model to classify leaves from the leaf classification dataset on Kaggle. After I compiled and trained the model, I used it to predict the name of the leaves in the testing images, but all I got is an array of integers. How can I exactly interpret those numbers in order to get the n... | https://datascience.stackexchange.com/questions/65421/how-to-interpret-predicted-data-from-a-keras-model |
Question: <p>What is the significance of the macro avg? I'm not sure if this report signifies a good prediction by the model.</p>
<p><a href="https://i.sstatic.net/YSnAU.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/YSnAU.png" alt="enter image description here" /></a></p>
Answer: <p>Your model is dece... | https://datascience.stackexchange.com/questions/93117/how-to-interpret-classification-output-predective-model |
Question: <p>I need some help to understand if the models are overfitting and which of these we can consider "the best". On the internet i only find simple examples with learning curves but in these cases i'm not sure to interpret them, so thank you in advance. It's a binary classification problem, the classe... | https://datascience.stackexchange.com/questions/117369/interpreting-learning-curves-of-models |
Question: <p>I was trying to use <code>Shapley value</code> approach for understanding the model predictions. I am trying this on a <code>Xgboost</code> model. My plot looks like as below</p>
<p><a href="https://i.sstatic.net/lGb7V.png" rel="noreferrer"><img src="https://i.sstatic.net/lGb7V.png" alt="enter image descr... | https://datascience.stackexchange.com/questions/65307/how-to-interpret-shapley-value-plot-for-a-model |
Question: <p>I'm working on a multi-classification problem - <a href="https://www.kaggle.com/alxmamaev/flowers-recognition" rel="noreferrer">Recognizing flowers</a>. </p>
<p>I trained the mode and I achieved accuracy of 0.99.</p>
<p>To predict, I did:</p>
<pre><code>a = model.predict(train[:6])
</code></pre>
<p>out... | https://datascience.stackexchange.com/questions/37722/how-to-interpret-predictions-from-model |
Question: <p>I am reading these articles (see below), which advocate the use of numerical encoding rather than one hot encoding for better interpretability of feature importance output from ensemble models. This goes against everything I have learnt - won't Python treat nominal features (like cities, car make/model) as... | https://datascience.stackexchange.com/questions/106673/can-numerical-encoding-really-replace-one-hot-encoding |
Question: <p>I am wondering about other interpretable models apart from logistic regression.</p>
<p>I am looking for models that can interpret the effect on the target variable by unit change in any feature variable.</p>
<p>I was thinking tree-based models may help but I'm not sure.</p>
Answer: | https://datascience.stackexchange.com/questions/66066/interpretable-models-apart-from-logistic-regression |
Question: <p>I am trying to evaluate a regression model (random forests); my understanding is that R^2 (coefficient of determination) is not a good measure of fitness since my dataset is non-linear. It looks like RMSE is the usual choice, but how do I know what is a 'good' value? Furthermore, it seems that RMSE is sens... | https://datascience.stackexchange.com/questions/126593/how-to-interpret-rmse-to-evaluate-a-regression-model |
Question: <p>There are multiple techniques to analyze the feature importance (permutations, SHAP values, etc).</p>
<p>It is essential that, in order to improve the interpretability of the model, we can somehow map the transformed features to the original ones. For example, when we assess the feature importance of enco... | https://datascience.stackexchange.com/questions/67455/how-can-we-assess-the-importance-of-the-features-even-if-we-ended-up-applying-pc |
Question: <p>I'm working on a simple linear regression model to predict 'Label' based on 'feature'. The two variables seems to be highly correlate corr=0.99. After splitting the data sample for to training and testing sets. I make predictions and evaluate the model.</p>
<pre><code>metrics.mean_squared_error(Label_test,... | https://datascience.stackexchange.com/questions/90396/how-to-interpret-the-mean-squared-error-value-in-a-regression-model |
Question: <p>I need some help in Interpreting a curve val_loss and loss in keras after training a model</p>
<p>These are the learning curves:
<a href="https://i.sstatic.net/gdmMw.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/gdmMw.png" alt="after 100 epoch of training " /></a></p>
Answer: <p>The tr... | https://datascience.stackexchange.com/questions/111721/interpreting-a-curve-val-loss-and-loss-in-keras-after-training-a-model-help |
Question: <p><a href="https://i.sstatic.net/mHbeh.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/mHbeh.png" alt="enter image description here" /></a></p>
<p>I have the following linear regression model and its analysis. There are a few errors, but I am not very sure about the errors. I have not succeede... | https://datascience.stackexchange.com/questions/77823/how-do-i-interpret-the-output-of-linear-regression-model-in-r |
Question: <p>I have a GradientBoostingRegressor from <code>scikit-learn</code> which I trained. Afterwards, I obviously would like to know how good the model is. So, on a non-scaled dataset I would just use the <code>mean_squared_error</code> function from scikit and it would output a certain value that made sense (reg... | https://datascience.stackexchange.com/questions/51323/how-to-interpret-metrics-of-a-model-after-scaling-the-data |
Question: <p>One benefit of creating a linear model is that you can look at the coefficients the model learns and interpret them. For example, you can see which features have the most predictive power and which do not.</p>
<p>How, if at all, does feature interpretability change if we normalize (scale all features to 0-... | https://datascience.stackexchange.com/questions/80624/how-do-standardization-and-normalization-impact-the-coefficients-of-linear-model |
Question: <p>I have trained an artificial neural network (ANN) model using PyTorch that accurately predicts a scalar output based on three input tensors with the following shapes:</p>
<p>Input 1: (3600, 3)
Input 2: (10001, 3)
Input 3: (1,)
Output: (1,) float64</p>
<p>The model architecture includes fully connected laye... | https://datascience.stackexchange.com/questions/129910/methods-to-interpret-physical-relationships-between-inputs-and-output-in-a-train |
Question: <p><a href="https://statmodeling.stat.columbia.edu/2018/10/30/explainable-ml-versus-interpretable-ml/" rel="noreferrer">O’Rourke</a> says that explainable ML uses a black box model and explains it afterwards, whereas interpretable ML uses models that are no black boxes.</p>
<p><a href="https://christophm.git... | https://datascience.stackexchange.com/questions/70164/what-is-the-difference-between-explainable-and-interpretable-machine-learning |
Question: <p><a href="https://i.sstatic.net/W0JuB.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/W0JuB.png" alt="mu"></a></p>
<p><a href="https://i.sstatic.net/Osp3x.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/Osp3x.png" alt="ee"></a></p>
<p>I am having trouble understanding the cur... | https://datascience.stackexchange.com/questions/58506/interpreting-a-curve-val-loss-and-loss-in-keras-after-training-a-model |
Question: <p>Following a Tensorflow time series analysis <a href="https://www.tensorflow.org/tutorials/structured_data/time_series" rel="nofollow noreferrer">tutorial</a>, I came across a particular way of converting data timestamps into a time-of-day periodic signal, that could help the model interpret the data better... | https://datascience.stackexchange.com/questions/107215/feature-engineering-of-timestamp-for-time-series-analysis |
Question: <p>I have a relatively small dataset n = 500 for which I am training a CART decision tree.
My dataset has about 30 variables and the outcome has 3 classes.
<a href="https://i.sstatic.net/LbmUp.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/LbmUp.png" alt="enter image description here" /></a></... | https://datascience.stackexchange.com/questions/114309/how-to-perform-bootstrap-validation-on-cart-decision-tree |
Question: <p>I made two models of neural networks(different architectures), the first one gave me as result:</p>
<ul>
<li><p>Training Loss: 0.4195</p>
</li>
<li><p>Training Acc: 0.8325</p>
</li>
<li><p>Training Recall: 0.7266</p>
</li>
<li><p>Validation Loss: 0.4331</p>
</li>
<li><p>Validation Acc: 0.8483</p>
</li>
<li... | https://datascience.stackexchange.com/questions/80564/how-to-compare-and-interpret-results-of-two-neural-networks-models |
Question: <p>I'm using an XGBoost model for multi-class classification and is looking at feature importance by using SHAP values. I'm curious if multicollinarity is a problem for the interpretation of the SHAP values? As far as I know, XGB is not affected by multicollinarity, so I assume SHAP won't be affected due to t... | https://datascience.stackexchange.com/questions/111255/is-multicollinarity-a-problem-when-interpreting-shap-values-from-an-xgboost-mode |
Question: <p>I'm following this tutorial <a href="https://www.datascience.com/blog/introduction-to-forecasting-with-arima-in-r-learn-data-science-tutorials" rel="nofollow noreferrer">here</a> to build an ARIMA model in R. </p>
<p>I've done a Forecast using a fitted model in R. I specified the forecast horizon h period... | https://datascience.stackexchange.com/questions/53222/how-to-interpret-the-graph-representing-the-fit-provided-by-the-arima-model |
Question: <p>I'm following <em>Introduction to Machine Learning with Python: A Guide for Data Scientists</em> by Andreas C. Müller and Sarah Guido, and in Chapter 2 a demonstration of applying <code>LinearSVC()</code> is given. The result of classifying three blobs is shown in this screenshot:</p>
<p><a href="https:/... | https://datascience.stackexchange.com/questions/17970/how-can-i-know-how-to-interpret-the-output-coefficients-coefs-from-the-mode |
Question: <p>After fitting a decision tree with some continuous variable, how do I interpret the effect that variable has on the target?</p>
<p>For example I'm predicting target Y. From sklearn random forest or Xgboost I can find out that the feature X is important. How do I determine if feature X's correlation to Y i... | https://datascience.stackexchange.com/questions/23247/how-to-interpret-continuous-variables-in-a-decision-tree-model |
Question: <p>I am new to the concept of model interpretability using LIME method. I am following the tutorial <a href="https://www.mathworks.com/help/deeplearning/ug/investigate-spectrogram-classifications-using-lime.html" rel="nofollow noreferrer">LIME for spectrogram classification</a>. I am finding hard to understan... | https://datascience.stackexchange.com/questions/93687/beginner-level-how-to-interpret-lime-and-classification-result |
Question: <p>on the back of this topic (<a href="https://datascience.stackexchange.com/questions/36404/when-to-remove-correlated-variables">When to remove correlated variables</a>) I feel a follow up is needed, with the focus here being on raw performance and risk of distribution shift.</p>
<p>assuming little to medium... | https://datascience.stackexchange.com/questions/93899/correlated-variables-model-performance-optimal-trade-off |
Question: <p>I was thinking. Would it be a good approach to check your features one by one (assuming you have a manageable amount of them) and see the relationship they have with your target variable, if they have a non linear relationship then transform each of those features using their appropriate function for each... | https://datascience.stackexchange.com/questions/56874/for-a-regression-model-can-you-transform-all-your-features-to-linear-to-make-a |
Question: <p>There are some models such as PCA or SVM where scaling and centering of training data is essential.</p>
<p>There are some models, mostly tree-based where scaling and centering is not required at all.</p>
<p>I don't think some of the linear models like linear or logistic regression need it. But I could be w... | https://datascience.stackexchange.com/questions/112340/when-is-scaling-and-centering-important |
Question: <p>One of the researchers, Marco Ribeiro, who developed this method of explaining how black box models make their decisions has developed a Python implementation of the algorithm available through Github, but has anyone developed a R package? If so, can you report on using it?</p>
Answer: <p>I think you're t... | https://datascience.stackexchange.com/questions/17791/is-there-an-r-package-for-locally-interpretable-model-agnostic-explanations |
Question: <p><a href="https://i.sstatic.net/eeSVj.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/eeSVj.png" alt="Importance" /></a></p>
<p>A random forest model outputs the following importance values. How do I interpert them for feature selection? If it's the mean decreased accuracy does that mean that... | https://datascience.stackexchange.com/questions/110184/how-to-interpret-importance-of-random-forest-model-mean-decrease-accuracy-and-m |
Question: <p>I have built a binary classification model using:</p>
<ul>
<li>logit</li>
<li>decision trees</li>
<li>random forest</li>
<li>bagging classifier</li>
<li>gradientboost</li>
<li>xgboost</li>
<li>adaboost</li>
</ul>
<p>I have evaluated the above models and chose xgboost based on training/test and validation... | https://datascience.stackexchange.com/questions/41259/adding-recommendations-to-the-output-of-a-classification-model |
Question: <p>I am working with interaction features in my machine learning model, where I create new features by multiplying a numeric variable with an encoded categorical feature. My question is:</p>
<p>Should normalization be applied to these interaction terms? If yes, so should it be applied <strong>before interacti... | https://datascience.stackexchange.com/questions/130734/should-normalization-be-applied-on-interaction-feature |
Question: <p>In the field of machine learning, I'm wondering about the interest of applying feature selection techniques.</p>
<p>I mean, I often read articles or lectures speaking about how to reduce the number of feature (dimensionality reduction, PCA), how to select the best features (feature selection etc).</p>
<p... | https://datascience.stackexchange.com/questions/17244/feature-reduction-convenience |
Question: <p>I am using XGBoost for a machine learning model that learns from tabular data.</p>
<p>XGBoost uses boosting method on decision trees. When I look at the decision-making logic of decision trees, I notice the logic is based on 1 feature at one time. In real life, certain multiple features are related to ea... | https://datascience.stackexchange.com/questions/61125/how-to-tell-a-boosting-model-that-2-features-are-related-and-should-not-be-inter |
Question: <p>Feature scaling can be crucially necessary when using distance-, variance- or gradient-based methods (KNN, PCA, neural networks...), because depending on the case, it can improve the quality of results or the computational effort.</p>
<p>In some cases (tree-based models in particular), scaling has no impa... | https://datascience.stackexchange.com/questions/64302/when-should-i-not-scale-features |
Question: <p>I want to create a model in a food processing plant where my dependent variable is Electricity (KWhr) consumption per kg. Plant produce different food items with varying electricity consumption. I'm interested in knowing the impact of the proportion of each food item on consumption per kg.
so my model is</... | https://datascience.stackexchange.com/questions/107980/can-i-include-a-quotient-as-dependent-variable-and-independent-variables-with-sa |
Question: <p>I was training a Logistic Regression model over a fairly large dataset with ~1000 columns.</p>
<p>I did apply scaling of features using MinMaxScaler. </p>
<p>I was wondering how to interpret the coefficients generated by the model and find something like feature importance in a Tree based model. </p>
<p... | https://datascience.stackexchange.com/questions/63045/feature-importance-based-on-a-logistic-regression-model |
Question: <p>I am curious to if there is data available for MLP architectures in use today, their initial architecture, the steps that were taken to improve the architecture to an acceptable state and what the problem is the neural network aimed to solve.</p>
<p>For example, what the initial architecture (amount of hi... | https://ai.stackexchange.com/questions/14303/is-there-data-available-about-successful-neural-network-architectures |
Question: <p>I am currently studying the textbook <em>Neural Networks and Deep Learning</em> by Charu C. Aggarwal. In chapter <strong>1.2.1 Single Computational Layer: The Perceptron</strong>, the author says the following:</p>
<blockquote>
<p>Different choices of activation functions can be used to simulate different ... | https://ai.stackexchange.com/questions/24484/can-most-of-the-basic-machine-learning-models-be-easily-represented-as-simple-ne |
Question: <p>I tried the first neural network architecture and the second one, but keeping all other variables constants, I am getting better results with the second architecture. Why are these same neural network architecture giving different results? Or am I making some mistakes?</p>
<p><strong>First one:</strong></p... | https://ai.stackexchange.com/questions/22467/why-are-these-same-neural-network-architecture-giving-different-results |
Question: <p>With an RGB image of a paper sheet with text, I want to obtain an output image which is cropped and deskewed. Example of input:</p>
<p><a href="https://i.sstatic.net/l64Kn.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/l64Kn.png" alt="enter image description here" /></a></p>
<p>I have tried... | https://ai.stackexchange.com/questions/34685/image-in-image-out-neural-network-architectures |
Question: <p>When someone wants to compare 2 inputs, the most widespread idea is to use a Siamese architecture. Siamese architecture is a very high level idea, and can be customized based on the problem we are required to solve.</p>
<p><strong>Is there any other architecture type to compare 2 inputs ?</strong> </p>
<... | https://ai.stackexchange.com/questions/9169/neural-network-architecture-for-comparison |
Question: <p>I am building a neural network that takes in a set of 86 parameters (primarily architecture-related, such as building floor area, kitchen size, number of a certain type of furniture, etc.) and outputs a 4D mulitdimensional array of shape <code>(6, 2532, 39, 5)</code> containing vertices of path data that a... | https://ai.stackexchange.com/questions/41498/is-there-a-neural-network-architecture-specialized-for-mapping-lower-to-higher-d |
Question: <p>I have a use case where I will be inputting audio to a model, and the output of the model will be the same audio except with certain sounds removed (volume set to zero). The dataset is generated by taking an audio file, duplicating it, and then zeroing out the unwanted sounds (usually a half second long).... | https://ai.stackexchange.com/questions/38069/what-type-of-neural-network-architecture-allows-filtering-out-of-unwanted-sounds |
Question: <p>I am working in the following neural network architecture, I am using keras and TensorFlow as a back-end.</p>
<p>It is composed by the following, embedding of words, then I added a layer of
Long Short-Term Memory (LSTM) neural networks, one layer of output and finally. I am using the softmax activation f... | https://ai.stackexchange.com/questions/6215/is-the-following-neural-network-architecture-considered-deep-learning |
Question: <p>I am trying to do <strong>3d image deconvolution</strong> using <strong>convolution neural network</strong>. But I cannot find many famous CNNs that perform a 3d convolution. Can anyone point out some for me?</p>
<p>Background: I am using PyTorch, but any language is OK. What I want to know most is the net... | https://ai.stackexchange.com/questions/5979/which-neural-network-architectures-are-there-that-perform-3d-convolutions |
Question: <p>I am trying to set up a neural network architecture that is able to learn the points of one function (blue curves) from the points of an other one (red curves). I think that it could be somehow similar to the problem of learning a functional like it was described in this question <a href="https://stats.sta... | https://ai.stackexchange.com/questions/24852/neural-network-architecture-with-inputs-and-outputs-being-an-unkown-function-eac |
Question: <p>Imagine that a line divides an image in two regions which (slightly) differ in terms of texture and color. It is not a perfect, artificial line but rather a thin transition zone. I want to build a neural network which is able to infer geometrical information on this line (orientation and offset). The image... | https://ai.stackexchange.com/questions/6996/neural-network-architecture-for-line-orientation-prediction |
Question: <p>I have an image dataset where objects may belong to one of the hundred thousand classes.</p>
<p>What kind of neural network architecture should I use in order to achieve this?</p>
Answer: <p>Classification tasks with a large number of classes are usually handled with <a href="http://ruder.io/word-embeddi... | https://ai.stackexchange.com/questions/6880/what-kind-of-neural-network-architecture-do-i-use-to-classify-images-into-one-hu |
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