1200 pixels spectral datasets

In the Zip, spectral. npy was the average spectral data of red ginseng, mycotoxins and interference impurities, and label. npy was the corresponding label.  Spectral data format was [1200,510] and label data format was [1200,1].  The example of data usage (sklearn in Python database was used to establish the classification model) was as follows:

import numpy as npfrom sklearn. model_selection import train_test_splitfrom sklearn. preprocessing import StandardScalerfrom sklearn. neighbors import KNeighborsClassifierfrom sklearn. metrics import classification_report, accuracy_score

# Load spectral data and labelsx = np.load('.../spectral.npy')[:,1:-1]y = np.load('.../label.npy')

x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=42)

# Data standardizationscaler = StandardScaler()x_train = scaler.fit_transform(x_train)x_test = scaler.transform(x_test)

# Train the KNN modelknn_model = KNeighborsClassifier(n_neighbors=5) knn_model. fit(x_train, y_train)

# Predicty_pred = knn_model.predict(x_test)

# Print classification reports and accuracy ratesprint("Classification Report:")print(classification_report(y_test, y_pred))print("Accuracy Score:")print(accuracy_score(y_test, y_pred))