Tasty213
  • Member for 2 years, 6 months
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Force selecting samples in majority class with random forest
3 votes

I would suggest that you drop those 30 events and all 1's from your dataset (i presume you know which 30 they are). Then randomly select 584 samples from the remaining dataset and the stick it back ...

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svm.LinearSVC: larger max_iter number doesn't always increase the accuracy/precision/recall
Accepted answer
1 votes

When trying to find the optimum number of iterations it's normally quite useful to visualise how the increasing iteration effect the accuracy (can identify over-fitting and when you should stop ...

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Choice of f1 score for highly imbalanced dataset?
1 votes

To summarise this answer, Macro calculates and F1 score for each class then averages them. Micro calculates the recall/precision for each class, averages them then calculates the F1 score. Micro ...

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Matplotlib WIndow Not responding when loop is initialized
1 votes

The while True: loop will be causing the python interpreter to think there's something more to do. It will remain unresponsive until it 'finishes' that loop, which it will never do. Remove the Loop or ...

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Where can I find dataset for word analogy task?
1 votes

If i understand correctly you want a long text file of some sort that can easily be analysed. I would suggest that you use project Gutenberg which publishes thousands of free to use books in plain UTF-...

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Finding the usage percent to perform predictive analysis for new users
1 votes

Create a new column containing the % of times each user used the search bar (i'll call it chance) You could eliminate all users outside of 'n' standard deviations of the new column eliminate both ...

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Predicting probability for each tag given already chosen tags
1 votes

welcome to ML and data science. This is a classic situation where a RNN would be usefull. You could either train one from Keras yourself which would help you learn and get a better model but might ...

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Pandas DataFrame Rollup Error
1 votes

From my understanding you have dataframe containing a list of Buyer ID's, the product they bought and how many of it they bought. You want to find out what percentage of the total of each product ...

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Compare scores of models
1 votes

I'm going to assume your using python and scikit-learn mostly because it has a method for providing model metrics. from sklearn.metrics import classification_report # I presume that you've already ...

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Has this paper used weighted KNN or not?
0 votes

The reference for their KNN algorithm is Zhang et al. 2017, furthermore in their paper they reference that they are using the standard settings for the toolkit (k = 5 etc). In my understanding the ...

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How does one decide when to use boosting over bagging algorithm?
Accepted answer
0 votes

Bagging and boosting are two methods of implementing ensemble models. Bagging: each model is given the same inputs as every other and they all produce a model Boosting: the first model trains on the ...

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measuring flip-flop behaviour across several topics
0 votes

So I have a theory for this. We want to be able to distinguish users who are emotional and biased from those that are unemotional and unbiased. $$M = emotionality\\ B = Bias\\ t_i = tweet\ number\ i\\...

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Dealing with no data
0 votes

I would advise that you first of all have a good look at the data you currently have available then see what it looks like with the various standard data imputation methods. Secondly is temperature ...

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