When estimating the PD Model with Logistic Regression I am getting a Value error on the lecture code: " ValueError Traceback (most recent call last) <ipython-input-32-966f89d3c717> in <module> ----> 1 reg.fit(inputs_train, loan_data_targets_train) 2 # Estimates the coefficients of the object from the 'LogisticRegression' class 3 # with inputs (independent variables) contained in the first dataframe 4 # and targets (dependent variables) contained in the second dataframe. ~/opt/anaconda3/lib/python3.7/site-packages/sklearn/linear_model/_logistic.py in fit(self, X, y, sample_weight) 1525 1526 X, y = check_X_y(X, y, accept_sparse='csr', dtype=_dtype, order="C", -> 1527 accept_large_sparse=solver != 'liblinear') 1528 check_classification_targets(y) 1529 self.classes_ = np.unique(y) ~/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py in check_X_y(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator) 753 ensure_min_features=ensure_min_features, 754 warn_on_dtype=warn_on_dtype, --> 755 estimator=estimator) 756 if multi_output: 757 y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False, ~/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator) 576 if force_all_finite: 577 _assert_all_finite(array, --> 578 allow_nan=force_all_finite == 'allow-nan') 579 580 if ensure_min_samples > 0: ~/opt/anaconda3/lib/python3.7/site-packages/sklearn/utils/validation.py in _assert_all_finite(X, allow_nan, msg_dtype) 58 msg_err.format 59 (type_err, ---> 60 msg_dtype if msg_dtype is not None else X.dtype) 61 ) 62 # for object dtype data, we only check for NaNs (GH-13254) ValueError: Input contains NaN, infinity or a value too large for dtype('float64')"It works fine in the video lecture, but the same code won't run in jupyter. Can you help me please?

Hi Mariam, thanks for reaching out and sorry for the late response. Could you please provide a lecture link to the video, where you're experiencing difficulties? Thanks so much in advance! Best, 365 Eli

Hi I have the same error while fitting the logistic regression model. It is under PD model estimation

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Mariam Zakariadze

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February 16, 2021

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September 05, 2020

Credit Risk Modeling PD Model Estimation

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Elitsa Kaloyanova

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December 10, 2020

Oliver Kwan

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February 16, 2021

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