import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier


class Model:

    def __init__(self):
        scaler = StandardScaler()

    def train(self, X_train, Y_train, X_test, Y_test, n_range=40):
        error_rate = []
        # Might take some time
        for i in range(1, n_range):
            knn = KNeighborsClassifier(n_neighbors=i)
            knn.fit(X_train, Y_train)
            pred_i = knn.predict(X_test)
            error_rate.append(np.mean(pred_i != Y_test))