import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data"
sutunlar = ['sepal_uzunluk', 'sepal_genislik', 'petal_uzunluk',
'petal_genislik', 'sinif']
iris_df = pd.read_csv(url, names = sutunlar)
iris_df.head()
iris_df.info()
X = iris_df.iloc[:, :-1].values
y = iris_df.iloc[:, 4].values
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.20, random_state = 60) 
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
scaler.fit(X_train)
X_train = scaler.transform(X_train)
X_test = scaler.transform(X_test)
from sklearn.neighbors import KNeighborsClassifier
classifier = KNeighborsClassifier(n_neighbors = 5)
classifier.fit(X_train, y_train)
y_pred = classifier.predict(X_test)
print (y_pred)
from sklearn.metrics import classification_report, confusion_matrix
print(confusion_matrix(y_test, y_pred))
print(classification_report(y_test, y_pred))