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If you have two images, you first start to make histograms of the values (0-255) in the three color channels (red, green, and blue). In the article 25 bins are used, meaning that the values are assigned to one of 25 ranges. The second step is to then concatenate the the three single channel histograms to one histogram for the full image. Since each image ...


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That is indeed a drawback with grid search strategy, since you must know in advance each one of the possible combinations to try out, and that might be not optimal neither to get the best evaluation metric value nor in computation performance. You have other interesting strategies, not exhaustive hyperparameter search, for instance random search or based on ...


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Since your data is sequential, you could try with sequential models (LSTM, RNN, GRU) etc. With which you can you predict what the user will select after the set of books as recommendation. In this way the input sequence length can be anything. (like, 3345, 33456, 334567 etc). But to answer your question with KMeans. I assume, all the rows are in same length. ...


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