Code Wizard

Dataset type

Tabular

Use case

Model training and tuning

Model retraining

ML algorithm

Library used to train models

In which form is your dataset available?

File pandas DataFrame X and y numpy arrays

File type

CSV TSV NPY Parquet

Do you have separate file(s) or directory(ies) for the target and features?

No Yes

How is your data organized?

Single File Multiple Files Single Directory Multiple Directories

Do you have separate DataFrame for the target and features?

No Yes

Do you have a Single DataFrame / Multiple DataFrame?

Single DataFrame Multiple DataFrames

Do you have a Single numpy array?

Single numpy array Multiple numpy arrays

Warning

                    
                        from sklearn.preprocessing import LabelEncoder
                        from scipy.sparse import issparse
                        from scipy import sparse
                        def sensitivity_logit(X, y, w=None, *, sketch_size=None, use_y=True, class_weight: Dict[Any, float] = None):
                            """
                            Logit sampling from 2018 Paper On Coresets for Logistic Regression.
                            """
                            X = np.concatenate([X, np.ones([X.shape[0], 1])], axis=1)
                            if w is not None:
                                w = _check_sample_weight(w, X, dtype=X.dtype)
                                X, y = w_dot_X(X, y=y, w=w)
                            else:
                                w = _check_sample_weight(w, X, dtype=X.dtype)