Select training attributes and target

Required packages

You need below packages to use the code generated by recipe. All packages are automatically installed in MLJAR Studio.

pandas>=1.0.0

Python code

# Python code will be here

Example Python notebooks

Please find inspiration in example notebooks

• Train Random Forest regressor
• Visualize Decision Tree
• Decision Tree features importance
• Train Decision Tree classifier
• Train Decision Tree on Iris data set
• Train Decision Tree regressor
• Train Random Forest classifier
• Save and load Decision Tree
• Tune Decision Tree classifier
• MLJAR AutoML solution for Kaggle Playground series s4e6

Data wrangling cookbook

Code recipes from Data wrangling cookbook.

• DataFrame info
• DataFrame describe
• Display DataFrame
• Select X,y
• Select Columns
• Filter rows
• Delete Column
• Split to train/test
• Check missing values
• Drop rows with missing values
• Fill missing values
• Use imputer on new data
• Categorical to integer
• Use encoder on new data