Competition 1 (blog 1)
why! check the codes again please!! the question was utilizing ma.pdf
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why?! check the codes again please!! the question was utilizing machine learning in detecting fraud for credit card by logistic regression in artificial intelligence I A Import necessary tibnaries import pandas as pd from sklearn. model_selection import train_test_split from sklearn. linear_ nodel import LogisticRegression from sklearn.metrics import accuracy_score, confusion_matrix * Load the dataset data = pd.read_csv ( "creditcard.csv') * Split the dotoset into training and testing sets X_train, X_test, \( y_{\text {_train, }} y_{\text {_test = }} \) train_test_split(data.drop ("Class', axise1), data[ Cllass '], test_size-e.3, random_state-42 - Create the Logistic regression model model = Logistichegression( ) * Train the modet on the training data model.fit (x_train, \( y_{\text {_train) }} \) N Noke predictions on the testing data ypred= model, predict (xtest ) W Evaluate the performance of the model print ( "Accuracy Score:", accuracy_score (y_test, \( y_{\text {_pred) }} \) ) print ("Confusion Matrix: in", confusion_matrix(y_test, \( y_{\text {"_pred) }} \) )) FileNotfoundtrror Ce11 In[s], 1ine Traceback (nost recent call last) 5 froe sklearn, netrics import accuracy_score, confusion_natrix 7 ioad the datanet 10 i 5 plit the dataset into training and testing sets -statese42) unents. chocalsi, decorate.clocalis. wrapper (*args, "*kargs) 325 if len(arg5) i num_allow_args: stacklevelwind_stack_level(), uffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle dupe_cols, dtype, ongine, convecters, true values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, heep_default_na, na_filter. verbosa, skip.b FileNotFoundError: [Errno 2] No such file or directory: 'creditcard.csv'.
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why! check the codes again please!! the question was utilizing ma.pdf
- why?! check the codes again please!! the question was utilizing machine learning in detecting fraud for credit card by logistic regression in artificial intelligence I A Import necessary tibnaries import pandas as pd from sklearn. model_selection import train_test_split from sklearn. linear_ nodel import LogisticRegression from sklearn.metrics import accuracy_score, confusion_matrix * Load the dataset data = pd.read_csv ( "creditcard.csv') * Split the dotoset into training and testing sets X_train, X_test, ( y_{text {_train, }} y_{text {_test = }} ) train_test_split(data.drop ("Class', axise1), data[ Cllass '], test_size-e.3, random_state-42 - Create the Logistic regression model model = Logistichegression( ) * Train the modet on the training data model.fit (x_train, ( y_{text {_train) }} ) N Noke predictions on the testing data ypred= model, predict (xtest ) W Evaluate the performance of the model print ( "Accuracy Score:", accuracy_score (y_test, ( y_{text {_pred) }} ) ) print ("Confusion Matrix: in", confusion_matrix(y_test, ( y_{text {"_pred) }} ) )) FileNotfoundtrror Ce11 In[s], 1ine Traceback (nost recent call last) 5 froe sklearn, netrics import accuracy_score, confusion_natrix 7 ioad the datanet 10 i 5 plit the dataset into training and testing sets -statese42) unents. chocalsi, decorate.clocalis. wrapper (*args, "*kargs) 325 if len(arg5) i num_allow_args: stacklevelwind_stack_level(), uffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle dupe_cols, dtype, ongine, convecters, true values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, heep_default_na, na_filter. verbosa, skip.b FileNotFoundError: [Errno 2] No such file or directory: 'creditcard.csv'