Raja_yousuf
New Coder
Can anyone help me with the error when I use neural network:
<p>
import pandas as pd
from sklearn.naive_bayes import MultinomialNB
from sklearn.neural_network import MLPClassifier
from sklearn import tree
from sklearn.model_selection import train_test_split #to avoid overfitting
from sklearn import metrics
#import data
df = pd.read_csv("https://www.dropbox.com/s/0k5rzco88jflks4/group 7 6308 - employment new.csv?dl=1")
#features and target
features = ['Population','Gdp','Gdp growth','Inflation','Gas Price']
target = 'Employment'
#X and y data
x = df[features]
y = df[target]
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3,random_state=1)
#Model
model = MLPClassifier()
model.fit(x_train, y_train)
#predict
y_test_pred = model.predict(x_test)
#performance
print("coefficients: ", model.coef_)
print("constant term: ", model.intercept_)
print(metrics.r2_score(y_test, y_test_pred))</p>
<p>
import pandas as pd
from sklearn.naive_bayes import MultinomialNB
from sklearn.neural_network import MLPClassifier
from sklearn import tree
from sklearn.model_selection import train_test_split #to avoid overfitting
from sklearn import metrics
#import data
df = pd.read_csv("https://www.dropbox.com/s/0k5rzco88jflks4/group 7 6308 - employment new.csv?dl=1")
#features and target
features = ['Population','Gdp','Gdp growth','Inflation','Gas Price']
target = 'Employment'
#X and y data
x = df[features]
y = df[target]
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3,random_state=1)
#Model
model = MLPClassifier()
model.fit(x_train, y_train)
#predict
y_test_pred = model.predict(x_test)
#performance
print("coefficients: ", model.coef_)
print("constant term: ", model.intercept_)
print(metrics.r2_score(y_test, y_test_pred))</p>
