PCA for Food Classification with Python

Prerequisites

• Python 3.8+
• numpy, pandas, scikit-learn, matplotlib
• Basic understanding of PCA concepts

Step 1: Load the Data

import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
from sklearn.decomposition import PCA

data = pd.read_csv('food_spectra.csv')
X = data.iloc[:, 1:]
y = data['class']

Step 2: Preprocess

scaler = StandardScaler()
X_scaled = scaler.fit_transform(X)

Step 3: Apply PCA

pca = PCA(n_components=5)
X_pca = pca.fit_transform(X_scaled)
print(f'Explained variance: {pca.explained_variance_ratio_}')