Python Docs

Basic Machine Learning using Scikit-Learn

Scikit-Learn provides simple, consistent APIs for common machine learning algorithms such as classification, regression, and clustering, along with utilities for model selection and evaluation.

Quick Example: Logistic Regression on Iris Dataset

Below is a minimal example using LogisticRegression on the classic Iris dataset. We load the features and labels, fit a classifier, and print the training accuracy.

Example

from sklearn.linear_model import LogisticRegression
from sklearn.datasets import load_iris

X, y = load_iris(return_X_y=True)
clf = LogisticRegression(max_iter=200).fit(X, y)
print(clf.score(X, y))

Output (example):

0.97 # (Approx training accuracy, depends on solver & version)