Classification

Support Vector Classification (SVC) is a machine learning algorithm used for binary and multi-class classification tasks. In this example, I’ll provide a step-by-step guide for implementing Support Vector Classification in Python using Scikit-Learn: Step 1: Import Libraries import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from …

K-Nearest Neighbors (KNN) is a supervised machine learning algorithm used for classification and regression tasks. In this example, I’ll provide a step-by-step guide for implementing KNN classification in Python using Scikit-Learn: Step 1: Import Libraries import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from sklearn.neighbors import …

Naive Bayes is a simple yet effective supervised machine learning algorithm commonly used for classification tasks. In this example, I’ll provide a step-by-step guide for implementing Naive Bayes classification in Python using Scikit-Learn. There are different variants of Naive Bayes, such as Gaussian Naive Bayes for continuous data and Multinomial …

Random Forest Classification is an ensemble learning technique that combines multiple decision trees to improve classification accuracy and reduce overfitting. In Python, you can implement Random Forest Classification using Scikit-Learn. Here’s a step-by-step guide: Step 1: Import Libraries import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split …

Decision Tree Classification is a machine learning algorithm used for classifying data into multiple classes. In this example, I’ll provide a step-by-step guide for implementing Decision Tree Classification in Python using Scikit-Learn: Step 1: Import Libraries import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from sklearn.tree …

Logistic Regression is a widely used machine learning algorithm for binary classification tasks, where the goal is to predict one of two possible classes (e.g., yes/no, spam/not spam). In Python, you can implement Logistic Regression using Scikit-Learn. Here’s a step-by-step guide: Step 1: Import Libraries import numpy as np import …