In this ML Algorithms course tutorial, we are going to learn “ K Nearest Neighbor Regression in detail. we covered it by practically and theoretical intuition.
- What is K Nearest Neighbor?
- What does the K stand for in K nearest neighbors?
- What is K Nearest Neighbor used for?
- How do K Nearest Neighbor work?
- What is K Nearest Neighbor Regression?
- What is Euclidian Distance Manhattan Distance?
- What is nearest Neighbour rule?
- What is K Nearest Neighbor Regression diagram?
- How to implement K Nearest Neighbor Regression in python using sklearn?
K Nearest Neighbor Regression Project
"""
## Business Problem - Predict the Price of Bangalore House
**Using** K Nearest Neighbor Regression - Supervised Machine Learning Algorithm
### Load Libraries
"""
import pandas as pd
"""### Load Data"""
path = r"https://drive.google.com/uc?export=download&id=1xxDtrZKfuWQfl-6KA9XEd_eatitNPnkB"
df = pd.read_csv(path)
df.head()
"""## Split Data"""
X = df.drop('price', axis=1)
y = df['price']
print('Shape of X = ', X.shape)
print('Shape of y = ', y.shape)
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=51)
print('Shape of X_train = ', X_train.shape)
print('Shape of y_train = ', y_train.shape)
print('Shape of X_test = ', X_test.shape)
print('Shape of y_test = ', y_test.shape)
"""##K Nearest Neighbor Regression - ML Model Training"""
from sklearn.neighbors import KNeighborsRegressor
regressor = KNeighborsRegressor(n_neighbors=5)
regressor.fit(X_train, y_train)
regressor.score(X_test, y_test)
"""## Predict the value of Home"""
X_test.iloc[-1, :]
regressor.predict([X_test.iloc[-1, :]])
y_test.iloc[-1]
y_pred = regressor.predict(X_test)
y_pred
y_test