Ridge Classifier Python Example

ridgeclass.py

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import datasets
from sklearn.linear_model import RidgeClassifier
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
#
# Load IRIS dataset
#
iris = datasets.load_iris()
#
# Create dataframe from IRIS dataset
#
df = pd.DataFrame(iris.data, columns=["sepal_length", "sepal_width", "petal_length", "petal_width"])
df["class"] = iris.target
#
# Create training and test dataset
# As IRIS is multi-class dataset, only two classes (Setosa, Versicolour) have been
# taken into consideration for training purpose for testing
# binary classification
#
X_train, X_test, y_train, y_test = train_test_split(df.iloc[:,0:4],
                                                    df.iloc[:, -1],
                                                    test_size=0.3,
                                                    random_state=1,
                                                    stratify=df.iloc[:, -1])
#
# Create standardized training dataset
#
sc = StandardScaler()
X_train_norm = sc.fit_transform(X_train)
X_test_norm = sc.transform(X_test)
#
# Create RidgeClassifier instance
#
rdgclassifier = RidgeClassifier()
rdgclassifier.fit(X_train_norm, y_train)
#
# Score the classifier
#
rdgclassifier.score(X_test_norm, y_test)