repo_name stringlengths 6 103 | path stringlengths 4 209 | copies stringclasses 325
values | size stringlengths 4 7 | content stringlengths 838 1.04M | license stringclasses 15
values |
|---|---|---|---|---|---|
CCI-Tools/cate-core | cate/ops/utility.py | 1 | 12435 | # The MIT License (MIT)
# Copyright (c) 2016, 2017 by the ESA CCI Toolbox development team and contributors
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of
# this software and associated documentation files (the "Software"), to deal in
# the Software without restriction, including wi... | mit |
marionleborgne/nupic.research | htmresearch/support/junit_testing.py | 9 | 8727 | #!/usr/bin/env python
# ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2016, Numenta, Inc. Unless you have purchased from
# Numenta, Inc. a separate commercial license for this software code, the
# following terms and conditio... | agpl-3.0 |
lilleswing/deepchem | examples/uv/UV_datasets.py | 8 | 4703 | """
UV dataset loader.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
import os
import shutil
import time
import numpy as np
import deepchem as dc
from uv_features import uv_descriptors
def remove_missing_entries(dataset):
"""Remove missing entries... | mit |
Athemis/lot | lot.py | 1 | 43683 | #!/usr/bin/env python
try:
import libtcodpy as libtcod
except ImportError:
raise ImportError('----- libtcod.py could not be loaded. -----')
import math
import textwrap
import shelve
try:
import numpy as np
except ImportError:
raise ImportError('----- NumPy must be installed. -----')
# actual size of ... | mit |
fx2003/tensorflow-study | TensorFlow实战/models/attention_ocr/python/data_provider_test.py | 18 | 2448 | # Copyright 2017 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | mit |
eadgarchen/tensorflow | tensorflow/python/keras/datasets/reuters/__init__.py | 71 | 1061 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
TinghuiWang/pyActLearn | examples/CASAS_Single_Test/b1_sda_raw.py | 1 | 8304 | import os
import pickle
import logging
import argparse
import numpy as np
import tensorflow as tf
from datetime import datetime
from pyActLearn.CASAS.data import CASASData
from pyActLearn.CASAS.fuel import CASASFuel
from pyActLearn.learning.nn.sda import SDA
from pyActLearn.performance.record import LearningResult
from... | bsd-3-clause |
jdanbrown/pydatalab | datalab/bigquery/_dataset.py | 6 | 8970 | # Copyright 2015 Google Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
# in compliance with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed ... | apache-2.0 |
elkingtonmcb/h2o-2 | py/testdir_hosts/test_parse_summary_zip_s3n_fvec.py | 9 | 2393 | import unittest, time, sys, random
sys.path.extend(['.','..','../..','py'])
import h2o, h2o_cmd, h2o_glm, h2o_browse as h2b, h2o_import as h2i
class Basic(unittest.TestCase):
def tearDown(self):
h2o.check_sandbox_for_errors()
@classmethod
def setUpClass(cls):
h2o.init(1)
@classmethod
... | apache-2.0 |
mlperf/training_results_v0.5 | v0.5.0/google/research_v3.32/gnmt-tpuv3-32/code/gnmt/model/t2t/tensor2tensor/data_generators/translate_encs.py | 3 | 3661 | # coding=utf-8
# Copyright 2018 The Tensor2Tensor Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | apache-2.0 |
fx2003/tensorflow-study | TensorFlow实战/models/inception/inception/image_processing.py | 14 | 20499 | # Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | mit |
Lawrence-Liu/crab | scikits/crab/recommenders/knn/neighborhood_strategies.py | 10 | 4860 | """
Strategies for users selection to be a
possible candidate to be member of a user neighborhood.
Please check the base.BaseUserNeighborhoodStrategy before
implement your own strategy.
"""
# Author: Marcel Caraciolo <marcel@muricoca.com>
#
# License: BSD Style.
from base import BaseUserNeighborhoodStrategy
import ... | bsd-3-clause |
marionleborgne/nupic.research | projects/imbu/engine/fluent_api.py | 11 | 6161 | # ----------------------------------------------------------------------
# Copyright (C) 2015, Numenta, Inc. Unless you have purchased from
# Numenta, Inc. a separate commercial license for this software code, the
# following terms and conditions apply:
#
# This program is free software: you can redistribute it and/or... | agpl-3.0 |
Diyago/Machine-Learning-scripts | DEEP LEARNING/segmentation/Kaggle TGS Salt Identification Challenge/v2/modules/functions.py | 1 | 10930 | import torch.autograd as autograd
import torch.cuda.comm as comm
from torch.autograd.function import once_differentiable
from . import _ext
# Activation names
ACT_LEAKY_RELU = "leaky_relu"
ACT_ELU = "elu"
ACT_NONE = "none"
def _check(fn, *args, **kwargs):
success = fn(*args, **kwargs)
if not success:
... | apache-2.0 |
shijx12/DeepSim | deepSimGAN/util.py | 1 | 8623 | from lib.datasets.factory import get_imdb
import numpy as np
import tensorflow as tf
import cv2
import random
import cfg
class DataFetcher:
def __init__(self, imdb_name, resize=True):
imdb = get_imdb(imdb_name)
# Ignore the background class!!! So ['gt_classes'] must minus 1.
self.classes = ... | mit |
lilleswing/deepchem | contrib/one_shot_models/multitask_regressor.py | 5 | 8197 | """
Implements a multitask graph-convolutional regression.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
__author__ = "Han Altae-Tran and Bharath Ramsundar"
__copyright__ = "Copyright 2016, Stanford University"
__license__ = "MIT"
import warnings
imp... | mit |
luo66/scikit-learn | sklearn/ensemble/tests/test_voting_classifier.py | 140 | 6926 | """Testing for the boost module (sklearn.ensemble.boost)."""
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from sklearn.ensemble import RandomForestCl... | bsd-3-clause |
LohithBlaze/scikit-learn | sklearn/metrics/regression.py | 174 | 16953 | """Metrics to assess performance on regression task
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Ma... | bsd-3-clause |
luo66/scikit-learn | examples/manifold/plot_manifold_sphere.py | 257 | 5101 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=============================================
Manifold Learning methods on a severed sphere
=============================================
An application of the different :ref:`manifold` techniques
on a spherical data-set. Here one can see the use of
dimensionality reducti... | bsd-3-clause |
jzt5132/scikit-learn | examples/cluster/plot_lena_segmentation.py | 269 | 2444 | """
=========================================
Segmenting the picture of Lena in regions
=========================================
This example uses :ref:`spectral_clustering` on a graph created from
voxel-to-voxel difference on an image to break this image into multiple
partly-homogeneous regions.
This procedure (spe... | bsd-3-clause |
mlperf/training_results_v0.5 | v0.5.0/google/cloud_v3.8/gnmt-tpuv3-8/code/gnmt/model/t2t/tensor2tensor/bin/t2t_datagen.py | 3 | 11111 | # coding=utf-8
# Copyright 2018 The Tensor2Tensor Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | apache-2.0 |
tomsilver/nupic | examples/opf/experiments/multistep/simple_3_enc/description.py | 17 | 1788 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | gpl-3.0 |
mlflow/mlflow | mlflow/prophet.py | 1 | 13361 | """
The ``mlflow.prophet`` module provides an API for logging and loading Prophet models.
This module exports univariate Prophet models in the following flavors:
Prophet (native) format
This is the main flavor that can be accessed with Prophet APIs.
:py:mod:`mlflow.pyfunc`
Produced for use by generic pyfunc-ba... | apache-2.0 |
elkingtonmcb/h2o-2 | py/testdir_ec2_only/test_KMeans_allstate_s3n_thru_hdfs.py | 9 | 2172 | import unittest, time, sys, random
sys.path.extend(['.','..','../..','py'])
import h2o, h2o_cmd, h2o_glm, h2o_kmeans, h2o_browse as h2b, h2o_import as h2i
class Basic(unittest.TestCase):
def tearDown(self):
h2o.check_sandbox_for_errors()
@classmethod
def setUpClass(cls):
# assume we're at ... | apache-2.0 |
LohithBlaze/scikit-learn | sklearn/decomposition/tests/test_dict_learning.py | 84 | 8565 | import numpy as np
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_raises... | bsd-3-clause |
fx2003/tensorflow-study | TensorFlow实战/models/lfads/synth_data/synthetic_data_utils.py | 3 | 10613 | # Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | mit |
luo66/scikit-learn | sklearn/feature_extraction/tests/test_feature_hasher.py | 256 | 2861 | from __future__ import unicode_literals
import numpy as np
from sklearn.feature_extraction import FeatureHasher
from nose.tools import assert_raises, assert_true
from numpy.testing import assert_array_equal, assert_equal
def test_feature_hasher_dicts():
h = FeatureHasher(n_features=16)
assert_equal("dict",... | bsd-3-clause |
LohithBlaze/scikit-learn | sklearn/linear_model/tests/test_coordinate_descent.py | 39 | 23697 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
from sys import version_info
import numpy as np
from scipy import interpolate, sparse
from copy import deepcopy
from sklearn.datasets import load_boston
from sklearn.utils.testing ... | bsd-3-clause |
MohammedWasim/scikit-learn | sklearn/datasets/tests/test_base.py | 204 | 5878 | import os
import shutil
import tempfile
import warnings
import nose
import numpy
from pickle import loads
from pickle import dumps
from sklearn.datasets import get_data_home
from sklearn.datasets import clear_data_home
from sklearn.datasets import load_files
from sklearn.datasets import load_sample_images
from sklearn... | bsd-3-clause |
glouppe/scikit-learn | examples/model_selection/plot_underfitting_overfitting.py | 51 | 2668 | """
============================
Underfitting vs. Overfitting
============================
This example demonstrates the problems of underfitting and overfitting and
how we can use linear regression with polynomial features to approximate
nonlinear functions. The plot shows the function that we want to approximate,
wh... | bsd-3-clause |
elkingtonmcb/h2o-2 | py/testdir_0xdata_only/test_hdfs_cdh5_fvec.py | 9 | 4072 | import unittest, time, sys, random
sys.path.extend(['.','..','../..','py'])
import h2o, h2o_cmd, h2o_browse as h2b, h2o_import as h2i, h2o_exec as h2e
import getpass
class Basic(unittest.TestCase):
def tearDown(self):
h2o.check_sandbox_for_errors()
@classmethod
def setUpClass(cls):
# assum... | apache-2.0 |
lilleswing/deepchem | contrib/one_shot_models/support_classifier.py | 6 | 14629 | """
Train support-based models.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
import warnings
import numpy as np
import tensorflow as tf
import sys
import time
from deepchem.models import Model
from deepchem.data import pad_batch
from deepchem.data im... | mit |
luo66/scikit-learn | examples/neural_networks/plot_rbm_logistic_classification.py | 257 | 4609 | """
==============================================================
Restricted Boltzmann Machine features for digit classification
==============================================================
For greyscale image data where pixel values can be interpreted as degrees of
blackness on a white background, like handwritten... | bsd-3-clause |
shyamalschandra/seastar | configure.py | 19 | 26249 | #!/usr/bin/python3
#
# This file is open source software, licensed to you under the terms
# of the Apache License, Version 2.0 (the "License"). See the NOTICE file
# distributed with this work for additional information regarding copyright
# ownership. You may not use this file except in compliance with the License.
... | apache-2.0 |
mlflow/mlflow | examples/shap/multiclass_classification.py | 1 | 1051 | import os
import numpy as np
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier
import shap
import mlflow
from mlflow.tracking import MlflowClient
from mlflow.artifacts import download_artifacts
# prepare training data
X, y = load_iris(return_X_y=True, as_frame=True)
# trai... | apache-2.0 |
elkingtonmcb/h2o-2 | py/testdir_single_jvm/test_ddply_plot.py | 8 | 9513 | import unittest, random, sys, time
sys.path.extend(['.','..','../..','py'])
import h2o, h2o_cmd, h2o_browse as h2b, h2o_import as h2i, h2o_gbm, h2o_jobs as h2j, h2o_import
import h2o_exec as h2e, h2o_util
import math
print "Copy a version of this to a two cloud test. different failure mode"
DO_PLOT = True
COL = 1
PHR... | apache-2.0 |
etalab/dactylo | dactylo/controllers/websockets.py | 1 | 3223 | # -*- coding: utf-8 -*-
# Dactylo -- A datasets activity streams logger
# By: Emmanuel Raviart <emmanuel@raviart.com>
#
# Copyright (C) 2013 Etalab
# http://github.com/etalab/dactylo
#
# This file is part of Dactylo.
#
# Dactylo is free software; you can redistribute it and/or modify
# it under the terms of the GNU A... | agpl-3.0 |
manipopopo/tensorflow | tensorflow/contrib/learn/python/learn/preprocessing/categorical.py | 40 | 4795 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
lukeiwanski/tensorflow | tensorflow/examples/tutorials/layers/cnn_mnist.py | 42 | 5711 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | apache-2.0 |
diekhans/ga4gh-server | scripts/prepare_compliance_data.py | 4 | 6553 | """
A script that takes the compliance dataset (the released version
of which is at https://github.com/ga4gh/compliance/tree/master/test-data)
and turns it into a directory bundle of binary and JSON files suitable
for use by the reference server.
"""
from __future__ import division
from __future__ import print_function... | apache-2.0 |
elkingtonmcb/h2o-2 | py/testdir_multi_jvm/test_GLM2_covtype_exec.py | 9 | 2344 | import unittest, time, sys, random
sys.path.extend(['.','..','../..','py'])
import h2o, h2o_cmd, h2o_glm, h2o_import as h2i
class Basic(unittest.TestCase):
def tearDown(self):
h2o.check_sandbox_for_errors()
@classmethod
def setUpClass(cls):
h2o.init(3,java_heap_GB=4)
@classmethod
... | apache-2.0 |
glouppe/scikit-learn | examples/plot_kernel_ridge_regression.py | 14 | 6227 | """
=============================================
Comparison of kernel ridge regression and SVR
=============================================
Both kernel ridge regression (KRR) and SVR learn a non-linear function by
employing the kernel trick, i.e., they learn a linear function in the space
induced by the respective k... | bsd-3-clause |
chetan51/nupic | examples/opf/experiments/missing_record/make_datasets.py | 9 | 4817 | #! /usr/bin/env python
# ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions... | gpl-3.0 |
kylerbrown/scikit-learn | sklearn/cluster/tests/test_dbscan.py | 113 | 11393 | """
Tests for DBSCAN clustering algorithm
"""
import pickle
import numpy as np
from scipy.spatial import distance
from scipy import sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing im... | bsd-3-clause |
olt/mapproxy | mapproxy/config/loader.py | 1 | 80871 | # This file is part of the MapProxy project.
# Copyright (C) 2010-2016 Omniscale <http://omniscale.de>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | apache-2.0 |
xyguo/scikit-learn | sklearn/decomposition/base.py | 310 | 5647 | """Principal Component Analysis Base Classes"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Kyle Kastner <kastnerkyle@gmail.com>
#
# Licen... | bsd-3-clause |
google/uncertainty-baselines | experimental/language_structure/vrnn/linear_vae_cell.py | 1 | 24349 | # coding=utf-8
# Copyright 2022 The Uncertainty Baselines Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | apache-2.0 |
kylerbrown/scikit-learn | benchmarks/bench_mnist.py | 153 | 6006 | """
=======================
MNIST dataset benchmark
=======================
Benchmark on the MNIST dataset. The dataset comprises 70,000 samples
and 784 features. Here, we consider the task of predicting
10 classes - digits from 0 to 9 from their raw images. By contrast to the
covertype dataset, the feature space is... | bsd-3-clause |
dsquareindia/scikit-learn | examples/cluster/plot_face_ward_segmentation.py | 70 | 2460 | """
=========================================================================
A demo of structured Ward hierarchical clustering on a raccoon face image
=========================================================================
Compute the segmentation of a 2D image with Ward hierarchical
clustering. The clustering is s... | bsd-3-clause |
dsquareindia/scikit-learn | sklearn/utils/__init__.py | 13 | 13265 | """
The :mod:`sklearn.utils` module includes various utilities.
"""
from collections import Sequence
import numpy as np
from scipy.sparse import issparse
import warnings
from .murmurhash import murmurhash3_32
from .validation import (as_float_array,
assert_all_finite,
... | bsd-3-clause |
yavuzovski/playground | machine learning/Udacity/ud120-projects/choose_your_own/your_algorithm.py | 1 | 2434 | #!/usr/bin/python
from time import time
import matplotlib.pyplot as plt
from prep_terrain_data import makeTerrainData
from class_vis import prettyPicture
features_train, labels_train, features_test, labels_test = makeTerrainData()
### the training data (features_train, labels_train) have both "fast" and "slow"
### p... | gpl-3.0 |
xyguo/scikit-learn | examples/applications/plot_out_of_core_classification.py | 31 | 13829 | """
======================================================
Out-of-core classification of text documents
======================================================
This is an example showing how scikit-learn can be used for classification
using an out-of-core approach: learning from data that doesn't fit into main
memory. ... | bsd-3-clause |
xyguo/scikit-learn | examples/cluster/plot_cluster_iris.py | 347 | 2593 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
K-means Clustering
=========================================================
The plots display firstly what a K-means algorithm would yield
using three clusters. It is then shown what the effect of a bad
initializa... | bsd-3-clause |
dsquareindia/scikit-learn | sklearn/ensemble/forest.py | 8 | 67993 | """Forest of trees-based ensemble methods
Those methods include random forests and extremely randomized trees.
The module structure is the following:
- The ``BaseForest`` base class implements a common ``fit`` method for all
the estimators in the module. The ``fit`` method of the base ``Forest``
class calls the ... | bsd-3-clause |
ChanChiChoi/scikit-learn | examples/applications/svm_gui.py | 285 | 11161 | """
==========
Libsvm GUI
==========
A simple graphical frontend for Libsvm mainly intended for didactic
purposes. You can create data points by point and click and visualize
the decision region induced by different kernels and parameter settings.
To create positive examples click the left mouse button; to create
neg... | bsd-3-clause |
fredhusser/scikit-learn | sklearn/metrics/cluster/unsupervised.py | 228 | 8281 | """ Unsupervised evaluation metrics. """
# Authors: Robert Layton <robertlayton@gmail.com>
#
# License: BSD 3 clause
import numpy as np
from ...utils import check_random_state
from ..pairwise import pairwise_distances
def silhouette_score(X, labels, metric='euclidean', sample_size=None,
random... | bsd-3-clause |
fredhusser/scikit-learn | sklearn/__check_build/__init__.py | 342 | 1671 | """ Module to give helpful messages to the user that did not
compile the scikit properly.
"""
import os
INPLACE_MSG = """
It appears that you are importing a local scikit-learn source tree. For
this, you need to have an inplace install. Maybe you are in the source
directory and you need to try from another location.""... | bsd-3-clause |
ishanic/scikit-learn | sklearn/metrics/cluster/unsupervised.py | 228 | 8281 | """ Unsupervised evaluation metrics. """
# Authors: Robert Layton <robertlayton@gmail.com>
#
# License: BSD 3 clause
import numpy as np
from ...utils import check_random_state
from ..pairwise import pairwise_distances
def silhouette_score(X, labels, metric='euclidean', sample_size=None,
random... | bsd-3-clause |
ChanChiChoi/scikit-learn | examples/ensemble/plot_voting_decision_regions.py | 228 | 2386 | """
==================================================
Plot the decision boundaries of a VotingClassifier
==================================================
Plot the decision boundaries of a `VotingClassifier` for
two features of the Iris dataset.
Plot the class probabilities of the first sample in a toy dataset
pred... | bsd-3-clause |
ChanChiChoi/scikit-learn | sklearn/tests/test_common.py | 126 | 7665 | """
General tests for all estimators in sklearn.
"""
# Authors: Andreas Mueller <amueller@ais.uni-bonn.de>
# Gael Varoquaux gael.varoquaux@normalesup.org
# License: BSD 3 clause
from __future__ import print_function
import os
import warnings
import sys
import pkgutil
from sklearn.externals.six import PY3
fr... | bsd-3-clause |
andrewnc/scikit-learn | sklearn/cluster/tests/test_hierarchical.py | 228 | 19795 | """
Several basic tests for hierarchical clustering procedures
"""
# Authors: Vincent Michel, 2010, Gael Varoquaux 2012,
# Matteo Visconti di Oleggio Castello 2014
# License: BSD 3 clause
from tempfile import mkdtemp
import shutil
from functools import partial
import numpy as np
from scipy import sparse
from... | bsd-3-clause |
ishanic/scikit-learn | sklearn/cluster/tests/test_hierarchical.py | 228 | 19795 | """
Several basic tests for hierarchical clustering procedures
"""
# Authors: Vincent Michel, 2010, Gael Varoquaux 2012,
# Matteo Visconti di Oleggio Castello 2014
# License: BSD 3 clause
from tempfile import mkdtemp
import shutil
from functools import partial
import numpy as np
from scipy import sparse
from... | bsd-3-clause |
ashhher3/pylearn2 | pylearn2/datasets/hdf5_deprecated.py | 30 | 13414 | """
Objects for datasets serialized in HDF5 format (.h5).
"""
__author__ = "Steven Kearnes"
__copyright__ = "Copyright 2014, Stanford University"
__license__ = "3-clause BSD"
try:
import h5py
except ImportError:
h5py = None
import numpy as np
from theano.compat.six.moves import xrange
import warnings
from py... | bsd-3-clause |
zxsted/scipy | scipy/stats/mstats_basic.py | 18 | 82304 | """
An extension of scipy.stats.stats to support masked arrays
"""
# Original author (2007): Pierre GF Gerard-Marchant
# TODO : f_value_wilks_lambda looks botched... what are dfnum & dfden for ?
# TODO : ttest_rel looks botched: what are x1,x2,v1,v2 for ?
# TODO : reimplement ksonesamp
from __future__ import divisi... | bsd-3-clause |
ChanChiChoi/scikit-learn | examples/svm/plot_svm_scale_c.py | 222 | 5375 | """
==============================================
Scaling the regularization parameter for SVCs
==============================================
The following example illustrates the effect of scaling the
regularization parameter when using :ref:`svm` for
:ref:`classification <svm_classification>`.
For SVC classificati... | bsd-3-clause |
google/uncertainty-baselines | experimental/cifar10_resnet20/main.py | 1 | 5433 | # coding=utf-8
# Copyright 2022 The Uncertainty Baselines Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | apache-2.0 |
fredhusser/scikit-learn | sklearn/utils/tests/test_sparsefuncs.py | 156 | 13799 | import numpy as np
import scipy.sparse as sp
from scipy import linalg
from numpy.testing import assert_array_almost_equal, assert_array_equal
from sklearn.datasets import make_classification
from sklearn.utils.sparsefuncs import (mean_variance_axis,
inplace_column_scale,
... | bsd-3-clause |
icoderaven/slytherin_dagger | src/linear_predictor.py | 1 | 4306 | #!/usr/bin/env python
import math
import numpy as np
import scipy
import scipy.linalg as la
import os
from sklearn import linear_model
class LinearPredictor:
def __init__(self):
self.m_w = 0
self.m_mean_x = 0
self.m_mean_y = 0
self.m_std_x = 1
# -------------------------... | bsd-3-clause |
mythsmith/veusz | veusz/plugins/field.py | 1 | 14590 | # Copyright (C) 2010 Jeremy S. Sanders
# Email: Jeremy Sanders <jeremy@jeremysanders.net>
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# ... | gpl-2.0 |
ChanChiChoi/scikit-learn | examples/decomposition/plot_sparse_coding.py | 246 | 3846 | """
===========================================
Sparse coding with a precomputed dictionary
===========================================
Transform a signal as a sparse combination of Ricker wavelets. This example
visually compares different sparse coding methods using the
:class:`sklearn.decomposition.SparseCoder` esti... | bsd-3-clause |
kylerbrown/scikit-learn | sklearn/metrics/metrics.py | 232 | 1262 | import warnings
warnings.warn("sklearn.metrics.metrics is deprecated and will be removed in "
"0.18. Please import from sklearn.metrics",
DeprecationWarning)
from .ranking import auc
from .ranking import average_precision_score
from .ranking import label_ranking_average_precision_score
fro... | bsd-3-clause |
golharam/rgtools | scripts/galaxy/api/load_data_with_metadata.py | 1 | 3466 | #!/usr/bin/env python
"""
This script scans a directory for files with companion '.json' files, then loads
the data from the file, and attaches the .json contents using the 'extended_metadata'
system in the library
Sample call:
python load_data_with_metadata.py <api_key> <api_url> /data/folder "API Imports"
NOTE: ... | lgpl-3.0 |
google/uncertainty-baselines | baselines/jft/active_learning.py | 1 | 32769 | # coding=utf-8
# Copyright 2022 The Uncertainty Baselines Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | apache-2.0 |
xyguo/scikit-learn | sklearn/tree/export.py | 14 | 16020 | """
This module defines export functions for decision trees.
"""
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Noel Dawe <noel@dawe.me>
# Satrajit Gosh <satrajit.ghosh@gmail.com>
# Trevor... | bsd-3-clause |
xyguo/scikit-learn | sklearn/utils/tests/test_multiclass.py | 33 | 13405 |
from __future__ import division
import numpy as np
import scipy.sparse as sp
from itertools import product
from sklearn.externals.six.moves import xrange
from sklearn.externals.six import iteritems
from scipy.sparse import issparse
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sp... | bsd-3-clause |
google/uncertainty-baselines | uncertainty_baselines/datasets/toxic_comments_test.py | 1 | 7250 | # coding=utf-8
# Copyright 2022 The Uncertainty Baselines Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | apache-2.0 |
ishanic/scikit-learn | examples/ensemble/plot_gradient_boosting_quantile.py | 385 | 2114 | """
=====================================================
Prediction Intervals for Gradient Boosting Regression
=====================================================
This example shows how quantile regression can be used
to create prediction intervals.
"""
import numpy as np
import matplotlib.pyplot as plt
from skle... | bsd-3-clause |
xyguo/scikit-learn | examples/applications/topics_extraction_with_nmf_lda.py | 37 | 3869 | """
=======================================================================================
Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation
=======================================================================================
This is an example of applying Non-negative Matrix ... | bsd-3-clause |
MichaelChatzidakis/Mn_Classifier_CNNs | test_digitized_spectra.py | 1 | 4604 | import glob
from keras.models import load_model
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import glob
import os
import sys
from train_crossval import load_data
from sklearn.model_selection import StratifiedKFold
from keras.utils import np_utils
def main(argv):
data_path = '/home/m... | mit |
ChanChiChoi/scikit-learn | examples/ensemble/plot_ensemble_oob.py | 257 | 3265 | """
=============================
OOB Errors for Random Forests
=============================
The ``RandomForestClassifier`` is trained using *bootstrap aggregation*, where
each new tree is fit from a bootstrap sample of the training observations
:math:`z_i = (x_i, y_i)`. The *out-of-bag* (OOB) error is the average er... | bsd-3-clause |
rigdenlab/conkit | conkit/misc/tests/test___init__.py | 1 | 4394 | """Testing facility for conkit.misc.__init__"""
__author__ = "Felix Simkovic"
__date__ = "10 Jan 2018"
import unittest
from conkit.misc import *
from sklearn.svm import SVC
from sklearn.preprocessing import StandardScaler
class TestMiscInit(unittest.TestCase):
def test_load_validation_model_1(self):
cl... | bsd-3-clause |
swethasubramanian/LungCancerDetection | src/models/predict_model.py | 2 | 6291 | """
A script to predict nodules using conv net model and for analysis of results
"""
import tflearn
from cnn_model import CNNModel
import tensorflow as tf
import pickle
import pandas as pd
import numpy as np
import h5py
from sklearn.metrics import roc_curve, auc, confusion_matrix
import itertools
import matplotli... | mit |
zachmayer/gensim | gensim/corpora/sharded_corpus.py | 63 | 35097 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Original author: Jan Hajic jr.
# Copyright (C) 2015 Radim Rehurek and gensim team.
# Licensed under the GNU LGPL v2.1 - http://www.gnu.org/licenses/lgpl.html
"""
This module implements a corpus class that stores its data in separate files called
"shards". This is a com... | lgpl-2.1 |
fredhusser/scikit-learn | sklearn/tests/test_metaestimators.py | 225 | 4954 | """Common tests for metaestimators"""
import functools
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.externals.six import iterkeys
from sklearn.datasets import make_classification
from sklearn.utils.testing import assert_true, assert_false, assert_raises
from sklearn.pipeline import Pipeline... | bsd-3-clause |
Averroes/statsmodels | statsmodels/formula/tests/test_formula.py | 29 | 4647 | from statsmodels.compat.python import iteritems, StringIO
import warnings
from statsmodels.formula.api import ols
from statsmodels.formula.formulatools import make_hypotheses_matrices
from statsmodels.tools import add_constant
from statsmodels.datasets.longley import load, load_pandas
import numpy.testing as npt
from... | bsd-3-clause |
elkingtonmcb/scikit-learn | sklearn/decomposition/tests/test_kernel_pca.py | 154 | 8058 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import (assert_array_almost_equal, assert_less,
assert_equal, assert_not_equal,
assert_raises)
from sklearn.decomposition import PCA, KernelPCA
from sklearn.datasets import mak... | bsd-3-clause |
scalyr/scalyr-agent-2 | scalyr_agent/third_party/pymysql/tests/test_SSCursor.py | 2 | 3766 | import sys
try:
from pymysql.tests import base
import pymysql.cursors
from pymysql.constants import CLIENT
except Exception:
# For local testing from top-level directory, without installing
sys.path.append('../pymysql')
from pymysql.tests import base
import pymysql.cursors
from pymysql.... | apache-2.0 |
jaor/python | bigml/api_handlers/modelhandler.py | 2 | 6695 | # -*- coding: utf-8 -*-
#pylint: disable=abstract-method
#
# Copyright 2014-2022 BigML
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | apache-2.0 |
raghavrv/scikit-learn | examples/linear_model/plot_sgd_loss_functions.py | 79 | 1234 | """
==========================
SGD: convex loss functions
==========================
A plot that compares the various convex loss functions supported by
:class:`sklearn.linear_model.SGDClassifier` .
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
def modified_huber_loss(y_true, y_pred):
z ... | bsd-3-clause |
elkingtonmcb/scikit-learn | doc/tutorial/text_analytics/skeletons/exercise_02_sentiment.py | 255 | 2406 | """Build a sentiment analysis / polarity model
Sentiment analysis can be casted as a binary text classification problem,
that is fitting a linear classifier on features extracted from the text
of the user messages so as to guess wether the opinion of the author is
positive or negative.
In this examples we will use a ... | bsd-3-clause |
frank-tancf/scikit-learn | sklearn/datasets/tests/test_kddcup99.py | 57 | 1336 | """Test kddcup99 loader. Only 'percent10' mode is tested, as the full data
is too big to use in unit-testing.
The test is skipped if the data wasn't previously fetched and saved to
scikit-learn data folder.
"""
import errno
from sklearn.datasets import fetch_kddcup99
from sklearn.utils.testing import assert_equal, S... | bsd-3-clause |
ecobost/pipeline | python/pipeline/temperature.py | 5 | 5751 | import datajoint as dj
from pipeline import experiment
from commons import lab
from datajoint.jobs import key_hash
import os
import numpy as np
from .utils import h5, signal
from .exceptions import PipelineException
from . import notify
schema = dj.schema('pipeline_temperature')
@schema
class Temperature(dj.Import... | lgpl-3.0 |
FCH808/FCH808.github.io | Intro to Machine Learning/ud120-projects/pca/eigenfaces.py | 5 | 4980 | """
===================================================
Faces recognition example using eigenfaces and SVMs
===================================================
The dataset used in this example is a preprocessed excerpt of the
"Labeled Faces in the Wild", aka LFW_:
http://vis-www.cs.umass.edu/lfw/lfw-funneled.tgz (2... | mit |
andrewcmyers/tensorflow | tensorflow/contrib/keras/python/keras/datasets/cifar.py | 84 | 1542 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
yonglehou/scikit-learn | examples/mixture/plot_gmm_selection.py | 247 | 3223 | """
=================================
Gaussian Mixture Model Selection
=================================
This example shows that model selection can be performed with
Gaussian Mixture Models using information-theoretic criteria (BIC).
Model selection concerns both the covariance type
and the number of components in th... | bsd-3-clause |
yonglehou/scikit-learn | sklearn/mixture/tests/test_gmm.py | 199 | 17427 | import unittest
import copy
import sys
from nose.tools import assert_true
import numpy as np
from numpy.testing import (assert_array_equal, assert_array_almost_equal,
assert_raises)
from scipy import stats
from sklearn import mixture
from sklearn.datasets.samples_generator import make_spd_ma... | bsd-3-clause |
ammarkhann/FinalSeniorCode | lib/python2.7/site-packages/scipy/stats/stats.py | 7 | 186886 | # Copyright 2002 Gary Strangman. All rights reserved
# Copyright 2002-2016 The SciPy Developers
#
# The original code from Gary Strangman was heavily adapted for
# use in SciPy by Travis Oliphant. The original code came with the
# following disclaimer:
#
# This software is provided "as-is". There are no expressed or... | mit |
Leminen/project_template_deeplearning | src/models/logreg_example.py | 1 | 7774 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 10 16:43:52 2017
@author: leminen
"""
import os
import tensorflow as tf
import matplotlib.pyplot as plt
import datetime
import argparse
import shlex
import src.utils as utils
import src.data.util_data as util_data
def hparams_parser_train(hparams... | mit |
nightjean/Deep-Learning | tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined_benchmark_test.py | 82 | 8976 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
deniszgonjanin/ckanext-bcgov | ckanext/bcgov/logic/action.py | 2 | 28743 | # Copyright 2015, Province of British Columbia
# License: https://github.com/bcgov/ckanext-bcgov/blob/master/license
import ckan.plugins.toolkit as toolkit
import logging
import datetime
import sqlalchemy
import ckan.logic as logic
import ckan.plugins as plugins
import smtplib
from time import time
import ckan.lib... | agpl-3.0 |
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