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Results tagged with machine-learning
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user 41922
Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.
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Pros and Cons of Positive Unlabeled learning?
I've been looking for papers that discuss the pros and cons of positive unlabeled learning but I haven't been able to find anything.
I'm looking to compare the general differences between creating a p …
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How to add more theta parameters into my logistic regression?
I am a complete beginner in machine learning and coding in python. I have been tasked with coding logistic regression from scratch in comparison with using sklearn. My question is, with my code below …
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Is using unsupervised learning to setup supervised classification reasonable?
I've got a biological dataset describing genes. The overall idea is that there are thousands of these genes to sort through, so if ML can rank them I can then know which should be going into the lab f …
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How to add bias consideration into logistic regression code?
I am a complete beginner in coding and machine learning, and I've been tasked with learning what's under the hood of logistic regression (so I have pieced together the python code below) but I've been …
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How many ways are there to check model overfitting?
I am running xgboost on a regression classification problem where the model is predicting a score of how likely a gene is to cause a disease from 0-1.
I try to avoid overfitting in all the ways I can …
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Feature selection for data with both continuous and categorical features?
I am working on a classification problem with 4 ordinal classes to predict, labelling/predicting samples as either a number from 1-4. My training dataset has 284 features by ~40,000 samples and I am l …
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How to interpret a specific feature importance?
Apologies for a very case specific question. I have a dataset of genes, with which I am using machine learning to predict if a gene causes a disease. One of the features I have is a beta value (which …
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How to make a classification problem into a regression problem?
I have data describing genes which each get 1 of 4 labels, I use this to train models to predict/label other unlabelled genes. I have a huge class imbalance with 10k genes in 1 label and 50-100 genes …
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How to assess nested cross validation results in comparison to non-nested results? [closed]
I have a nonlinear regression model scoring genes from scores between 0 to 1 as to whether they are likely to cause disease. Training data is ~700 gene samples by 53 features.
Currently I get results …
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How to decide on using xgboost with imputation or without it and keeping missing values?
I have a large genetic dataset that I am using xgboost on to score most likely disease causing genes - giving the genes a score between 0-1 of likelihood.
I try to avoid features with a lot of missi …
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