Getting started

This section demonstrates the usage of GATree for machine learning tasks.

Installation

To install GATree with pip, use:

pip install gatree

Usage

The following example demonstrates how to perform classification of the iris dataset using GATree.

import pandas as pd
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from gatree.methods.gatreeclassifier import GATreeClassifier

# Load the iris dataset
iris = load_iris()
X = pd.DataFrame(iris.data, columns=iris.feature_names)
y = pd.Series(iris.target, name='target')

# Split the dataset into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.2, random_state=10)

# Create and fit the GATree classifier
gatree = GATreeClassifier(n_jobs=16, random_state=32)
gatree.fit(X=X_train, y=y_train, population_size=100, max_iter=100)

# Make predictions on the testing set
y_pred = gatree.predict(X_test)

# Evaluate the accuracy of the classifier
print(accuracy_score(y_test, y_pred))