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I am using Xgboost for classification. My y is 0 or 1 (true or false). I have categorical and numeric features, so theoretically, I need to use SMOTE-NC instead of...
Asked on 01/06/2021 by RafalQA
1 answerI was reading about descending gradient.How does the descending gradient know what weights to adjust?Does it adjust to all network weights at the same time? Does each weight...
Asked on 01/06/2021 by molo32
2 answerWhen building a Pipeline I'm ending up at a scenario that can be simplified like this: FeatureUnion(NumericalPipeline(steps), CategoricalPipeline(steps)) Since this is one intermediary step in a larger Pipeline, I'm feeding...
Asked on 01/06/2021
1 answerI am new to both data science and python.I have a dataset of the time-dependent samples, which I want to run agglomerative hierarchical clustering on them. I have found...
Asked on 01/05/2021 by user3806649
1 answerOne thing that is really useful when trying to understand what a machine learning model does, is seeing why some instances got predicted. For that Shapley Values...
Asked on 01/05/2021
1 answerSuppose you have a population of N individuals with fitness 1, 2, . . . , N (i.e., all individuals have aunique fitness value). Suppose you repeatedly apply tournament...
Asked on 01/05/2021
1 answerI am new to machine learning. I want to develop a face recognition system using scikit-learn. This is the example given in the tutorials of scikit-learn. I...
Asked on 01/05/2021 by enterML
1 answerI do not understand how complex networks with many parameters/dimensions can be represented in a 3D space, and form a standard cost surface just like a simple network with, say,...
Asked on 01/05/2021 by forhayley
2 answerI found the following figure in the original Mish paper (https://arxiv.org/abs/1908.08681). I understand that this figure describes...
Asked on 01/05/2021 by shaurov2253
1 answerI have a small (~100 samples) dataset with roughly 20 features which are mostly binary, and a few are numeric (~5). I wanted to use methods for augmenting the training...
Asked on 01/05/2021 by S_S
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