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| # Tabular Classification / Regression | |
| Using AutoTrain, you can train a model to classify or regress tabular data easily. | |
| All you need to do is select from a list of models and upload your dataset. | |
| Parameter tuning is done automatically. | |
| ## Models | |
| The following models are available for tabular classification / regression. | |
| - xgboost | |
| - random_forest | |
| - ridge | |
| - logistic_regression | |
| - svm | |
| - extra_trees | |
| - gradient_boosting | |
| - adaboost | |
| - decision_tree | |
| - knn | |
| ## Data Format | |
| ```csv | |
| id,category1,category2,feature1,target | |
| 1,A,X,0.3373961604172684,1 | |
| 2,B,Z,0.6481718720511972,0 | |
| 3,A,Y,0.36824153984054797,1 | |
| 4,B,Z,0.9571551589530464,1 | |
| 5,B,Z,0.14035078041264515,1 | |
| 6,C,X,0.8700872583584364,1 | |
| 7,A,Y,0.4736080452737105,0 | |
| 8,C,Y,0.8009107519796442,1 | |
| 9,A,Y,0.5204774795512048,0 | |
| 10,A,Y,0.6788795301189603,0 | |
| . | |
| . | |
| . | |
| ``` | |
| ## Columns | |
| Your CSV dataset must have two columns: `id` and `target`. | |
| ## Parameters | |
| [[autodoc]] trainers.tabular.params.TabularParams | |