Mobile Price Classification

Helmi Sulaeman

Sosial Media


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Summary

in this project I will detect the classify of data price mobile

Description

Context

To find out some relation between features of a mobile phone( RAM,Internal Memory etc) and its selling price. 

Exploratory Data Set

Link = kaggle kernels output ibraheemseyam/mobile-price-classification-99 -p /path/to/dest

Train And Test Data  

Output

Comparing content between train and test data

Values in training data but not testing data:  n_cores []

Values in training data but not testing data:  blue []

Values in training data but not testing data:  dual_sim []

Values in training data but not testing data:  four_g []

Values in training data but not testing data:  three_g []

Values in training data but not testing data:  touch_screen []

Values in training data but not testing data:  wifi []

graph(df_train, 'price_range', 2)

 

#creating features

combine = [df_train, df_test] for dataset in combine:    dataset['total_pixels'] = dataset['px_height']*dataset['px_width']    dataset['screen_area']  = dataset['sc_h']      *dataset['sc_w']        

#short range connections like bluetooth or wifi can be inter-changable, if neither exist it is huge disadvantage    

dataset['connectivity'] = 0    dataset['connectivity'][dataset['blue']==1]=1    dataset['connectivity'][dataset['wifi']==1]=1

clf=setup(df_train,target='price_range') best = compare_models(sort = 'AUC',n_select=1, fold = 10) best_classifier=create_model(best) best_classifier_tuned = tune_model(best_classifier) plot_model(best_classifier_tuned,plot='feature')


Processing: 100% 69/69 [01:48<00:00, 2.70s/it]


Processing: 0% 0/4 [00:00<?, ?it/s]

#trying predictor on held-out data

predict_model(best_classifier_tuned)

#visualizing the predictions

pred_df = predict_model(model_mobile_price, data = df_test) pred_df['price_range']=pred_df['Label'] pred_df = pred_df.drop('Label', axis = 1) pred_df['dataset']='predictions' df_train['dataset']='training' merged_df = pd.concat([df_train, pred_df]).reset_index(drop=True) graph(merged_df, 'dataset')

Conclution

Informasi Course Terkait
  Kategori: Artificial Intelligence
  Course: Introduction Data Mining