Write a Python Program to implemen Support Vector Machines for data cl

Question

Write a Python Program to implemen Support Vector Machines for data classification, choose dataset of your own choice

07 Mar 2024

Answer :

Word Count : 581

Support Vector Machines (SVM) are a powerful tool for classification tasks. Let's implement an SVM classifier using the famous Iris dataset from sklearn. This dataset is commonly used for classification and consists of 150 samples with 4 features (sepal length, sepal width, petal length, and petal width).

Step-by-Step Implementation:
Load the Dataset: Use the Iris dataset provided by sklearn.
Preprocess the Data: Split the data into training and testing sets.
Train the SVM Model: Use SVC (Support Vector Classification) from `sklearn.
Evaluate the Model: Assess the model's performance using accuracy and a confusion matrix.
Visualize the Results: Plot decision boundaries if applicable.

Python Code:

import numpy as np
import matplotlib.pyplot as plt
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
from sklearn.preprocessing import StandardScaler
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