# Help with Machine Learning Project Walkthrough

Hi Everyone, i’ve been working on this project for a while. The problem i have is, when i try to find the tpr and fpr in my Jupyter notebook i have way different values than the ones i found in the site even if i have the same code in both windows

Site:

``````lr = LogisticRegression(class_weight="balanced")
predictions = cross_val_predict(lr, features, target, cv=3)
predictions = pd.Series(predictions)

fp_filter = (predictions == 1) & (loans['loan_status'] == 0)
fp = len(predictions[fp_filter])

tp_filter = (predictions == 1) & (loans['loan_status'] == 1)
tp = len(predictions[tp_filter])

fn_filter = (predictions == 0) & (loans['loan_status'] == 1)
fn = len(predictions[fn_filter])

tn_filter = (predictions == 0) & (loans['loan_status'] == 0)
tn = len(predictions[tn_filter])

fpr = fp / (fp + tn)
tpr = tp / (tp + fn)

print('False Positive Rate:', fpr)
print('True Positive Rate:', tpr)

False Positive Rate: 0.38664292074799644
True Positive Rate: 0.6636146617109359
``````

My code:

``````lr = LogisticRegression(class_weight="balanced")
predictions = cross_val_predict(lr, features, target, cv=3)
predictions = pd.Series(predictions)

fp_filter = (predictions == 1) & (loans_2007['loan_status'] == 0)
fp = len(predictions[fp_filter])

tp_filter = (predictions == 1) & (loans_2007['loan_status'] == 1)
tp = len(predictions[tp_filter])

fn_filter = (predictions == 0) & (loans_2007['loan_status'] == 1)
fn = len(predictions[fn_filter])

tn_filter = (predictions == 0) & (loans_2007['loan_status'] == 0)
tn = len(predictions[tn_filter])

fpr = fp / (fp + tn)
tpr = tp / (tp + fn)

print('False Positive Rate:', fpr)
print('True Positive Rate:', tpr)

False Positive Rate: 0.5237907206317868
True Positive Rate: 0.5465718405873099
``````

I don’t know if i’m doing something wrong or what or if there’s something wrong with the data
I also post my notebook in case someone wants to check everything i’ve done

`loans_2007` does not look like same code. How do you verify same code?