Update app.py

app.py

@@ -1,8 +1,5 @@
 import numpy as np
 import pandas as pd
-from sklearn.model_selection import train_test_split,cross_val_score
-from sklearn import datasets
-import scipy.stats as stats
 import xgboost as xgb
 import pandas as pd
 
@@ -12,12 +9,11 @@ import random
 
 x_strength=df_strength.iloc[:,:-1]
 y_strength=df_strength.iloc[:,-1]
-from sklearn.model_selection import train_test_split
-x_train, x_test, y_train, y_test=train_test_split(x_strength,y_strength, test_size=0.15, random_state=2)
+
 
 
 clf = XGBRegressor(learning_rate=0.1788, max_depth=27, subsample=0.5146, n_estimators=100)
-clf.fit(x_train, y_train)
+clf.fit(x_strength, y_strength)