Supervised Learning Algorithms in Machine Learning
k-Nearest Neighbors Algorithm
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from math import sqrt
plt.rcParams['font.sans-serif'] = ['Simhei']
wine_data = {'color_intensity': [14.13, 13.2, 13.16, 14.27, 13.24, 12.07, 12.43, 11.79, 12.37, 12.04],
'alcohol_content': [5.64, 4.28, 5.68, 4.80, 4.22, 2.76, 3.94 ...
Posted on Wed, 22 Jul 2026 16:30:59 +0000 by tyrol_gangster
Iris Species Classification Using K-Nearest Neighbors Algorithm
Dataset Overview
The Iris dataset, collected by Fisher in 1936, is a widely used classification dataset containing 150 samples from three iris species: Setosa, Versicolor, and Virginica. Each species has 50 samples with four features: sepal length, sepal width, petal length, and petal width.
In machine learning practice, data collection is typi ...
Posted on Mon, 01 Jun 2026 17:37:31 +0000 by 22Pixels
Wine Classification Using K-Nearest Neighbors in MindSpore
Overview
This guide demonstrates implementing a K-Nearest Neighbors classifier using MindSpore for the Wine dataset. We'll explore how to process chemical composition data to predict wine cultivars through distance-based classification.
Prerequisites
Before proceeding, ensure you have:
Python programming proficiency
Basic understanding of KNN ...
Posted on Fri, 15 May 2026 10:08:46 +0000 by Mikell