# 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