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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 | |