All Questions
7 questions
0
votes
1
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667
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F2 score or the Area under the Precision-Recall-Curve as a scoring metric
I have a dataset with which I want to perform binary classification.
The distribution of the target class is imbalanced: 20% positive labels, 80% negative labels.
The positive class is more important ...
- 145
2
votes
0
answers
467
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Why does precision_recall_curve() return similar but not equal values than confusion matrix?
INTRO: I wrote a very simple machine learning project which classifies numbers based on the minst dataset:
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- 212
7
votes
1
answer
1k
views
Adjusting classification thresholds based on test set predictions
I have a binary classifier that was trained using k-fold cross validation. I then use the model to get predictions on an unseen (held out) test data set. For my specific application, I would like a ...
- 1,334
1
vote
2
answers
294
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Classification: Random Forest vs. Decision tree
Suppose you are given a dataset with 4 attributes (F1, F2, F3, and F4). The class label is contained in attribute F4.
Now you build a random forest classification model and you test its performance ...
3
votes
1
answer
2k
views
Using micro average vs. macro average vs. normal versions of precision and recall for a binary classifier
I have a logistic regression recommender model built on my data where I tried to predict one of two outcomes for each row. Let's call them success and ...
- 399
2
votes
1
answer
5k
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Fail to improve recall in classification
I have a large data set with over 700,000 examples and I tried to (binary) classify the data set with Naive Bayes and Random Forest. The task was carried out in Python and Scikit-learn
data
The data ...
- 217
13
votes
1
answer
6k
views
Averaging precision and recall when using cross validation
I have performed classification using multiple classifiers for a 2-classes labelled data, and I used 5-fold cross validation. For each fold I calculated tp, tn, fp, and fn. Then I calculated the ...
- 355