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I was working with a dataset that had a textual column as well as numerical columns, so I used TFIDF for the textual column and created a sparse matrix, similarly...
Asked on 12/07/2021
1 answerI am reading "reinforcement learning - An introduction" by Sutton and Barto. At pag. 59, there is the Bellman equation for the state-value function $begin{array}{ll}v_{pi}(s) &=mathbb{E}_{pi}[G_t|S_t=s] \&=...
Asked on 12/07/2021
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 12/07/2021
2 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 12/05/2021
4 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 12/05/2021
3 answerI noticed that feature scaling can destroy completely neural networks performance in some cases. Below are my results that you can reproduce easily. I use a neural network to approximate...
Asked on 12/05/2021
1 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 12/05/2021
1 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 12/05/2021
1 answerI used quandl function extract stock data with object type as xts.a <- Quandl("NSE/ICICIBANK", start_date = "2011-01-01", end_date = "2019-02-21", collapse = "daily", type = "xts",order = "asc")...
Asked on 12/04/2021
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 12/04/2021
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