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I have a dataset similar to newsgroup20 for classification. With the training dataset, I have a dictionary data set that explains some jargons in the training dataset. These both are...
Asked on 08/27/2021
1 answerIn feature selection (for a regression problem), can features that are negatively correlated with the target variable be chosen to predict the target? I don't think negative correlation means...
Asked on 08/27/2021
2 answerI've little idea about choosing a ML approach for the following problem. It is a classification problem and there are 2 classes that are positive and negative. There are about...
Asked on 08/27/2021 by colt.exe
1 answerI have been using neural networks for a while now. However, one thing that I constantly struggle with is the selection of an optimizer for training the network (using backprop)....
Asked on 08/27/2021 by mplappert
4 answerI'm doing sentiment analysis on a twitter dataset (problem link). I have extracted the POS tags from the tweets and created tfidf vectors from the POS tags...
Asked on 08/27/2021
1 answerI'm currently studying GBDT and started reading LightGBM's research paper. In section 4. they explain the Exclusive Feature Bundling algorithm, which aims at reducing the number of...
Asked on 08/27/2021
3 answerI am executing this code which works perfectly for me: (I only have 'positive' and 'negative' sentiments):from sklearn import metricsprint('Accuracy:',metrics.accuracy_score(test_sentiments, predicted_sentiments)) print('Precision:',metrics.precision_score(test_sentiments, predicted_sentiments, pos_label='positive'))My question is: how come...
Asked on 08/27/2021
1 answerI have clustered vectors by cosine distance using nltk clusterer. If I understand correctly, Y axis for elbow method in euclidian distance would be the sum of every distance (squared)...
Asked on 08/26/2021 by Ruuza
1 answerWhen Implementing custom loss function how to make it invariant to the batch size. For example lets say dice loss is being implemented. The formula for dice loss is:...
Asked on 08/26/2021
0 answerI am analysing a technique "Sherlock" - a semantic type of column detecting technique wherein training dataset too many samples of a specific type are limited up...
Asked on 08/26/2021 by Zannatul Ferdaus
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