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First of all, if you are in a classification problem as you said, R2 score is not good, it should be used for regression problem. For classification problem you have to use something like accuracy, precision, recall and F1 score. First question Anyway, I will answer your first question about R2score: R2 mean: you are calculating the R2 for each split you ...


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If in each file the letters are spoken separately, with silence in between, and always in the same order (A,B...,Z) then one can try to automate finding each section and its label. Use a Voice Activity Detection (VAD) module to detect each spoken character. Then assign A to the first voiced area, B to the next etc. If you have very clean and uniform audio, ...


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Three separate models (one per channel) will easily learn to predict the >channel category, but it will never output r0g1b2 and r2g3b0 classes in 64 class model because it have never seen these classes. How to overcome this problem? The only way to solve this problem is to use channels (one for each skin damage type) for each pixel, and treat it as a ...


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The c (small one) term is bias or intercept added to the model. This is similar to intercept we add in case of linear regression. The library allows you to set bias term to zero too. When set to multinomial model, the cost function will try to minimize cross-entropy loss. Hard for me to write down the equation here, but I always go back to this useful ...


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using lstm or rnn's for time series data is like using a hammer to swat a fly. have you tried time series modeling using classical stat techniques ARCH, ARIMA etc ? the issue of using individual number as inputs (which is what your speedometer is going to give you) means that the states in each lstm / gru cell or unit will have like a 1x1 matrix , meaning 1 ...


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Gated recurrent units (GRUs) is an advanced version of RNN and LSTM. It has less time complexity and good prediction results than LSTM ann RNN. You can use it for dealing with time series dataset. You can boosted it performance by combining advanced version 1D CNN like ResNet, etc.


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Since I don't see the data and I cannot fully understand the data format, I am just giving some general advice. But first, I should mention that it doesn't make sense to consider each output (each 20-element array) as timeseries sequence unless there is a priority among them (by priority, I mean if you know a particular lab value is obtained before others) ...


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