Food order forecast by RandomForestRegressor, DecisionTreeRegressor, LinearRegression

 refer to code:

.

from sklearn.metrics import r2_score,mean_squared_error

from sklearn.ensemble import RandomForestRegressor

from sklearn.tree import DecisionTreeRegressor

from sklearn.linear_model import LinearRegression

from sklearn.model_selection import train_test_split

import matplotlib.pyplot as plt

import seaborn as sns

from math import sqrt

import numpy as np

import pandas as pd

import warnings

warnings.filterwarnings('ignore')

features = pd.read_csv('./features.csv')

label = pd.read_csv('./label.csv')

features.head()

label.head()

#------------------------------------ data split ---------------------------------------------

X_train,X_test,y_train,y_test = train_test_split(features,label,test_size=0.20,random_state=33)

#------------------------------------ RandomForestRegressor ---------------------------------------------

RFRmodel = RandomForestRegressor(max_depth=3, random_state=0)

RFRmodel.fit(X_train,y_train)

y_pred = RFRmodel.predict(X_test)

print('RandomForestRegressor')

print("R2 score :",r2_score(y_test, y_pred))

print("MSE score :",mean_squared_error(y_test, y_pred))

print("RMSE: ",sqrt(mean_squared_error(y_test, y_pred)))

print('')

#------------------------------------ DecisionTreeRegressor---------------------------------------------

DTRmodel = DecisionTreeRegressor(max_depth=3,random_state=0)

DTRmodel.fit(X_train,y_train)

y_pred = DTRmodel.predict(X_test)

print('DecisionTreeRegressor')

print("R2 score :",r2_score(y_test, y_pred))

print("MSE score :",mean_squared_error(y_test, y_pred))

print("RMSE: ",sqrt(mean_squared_error(y_test, y_pred)))

print('')

#------------------------------------ LinearRegression ---------------------------------------------

model = LinearRegression()

model.fit(X_train,y_train)

y_pred = model.predict(X_test)

print('LinearRegression')

print("R2 score :",r2_score(y_test, y_pred))

print("MSE score :",mean_squared_error(y_test, y_pred))

print("RMSE: ",sqrt(mean_squared_error(y_test, y_pred)))

print('')

..

You can download dataset from here:

https://www.marearts.com/Tea-Time-Computer-Vision-6bc925c53d46412691096825bfe0317a?p=004ca41eee0948c49f979016b6a31de8&pm=s

Thank you.

www.marearts.com

🙇🏻‍♂️