# Questions tagged [variance]

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### Co-joining multi-peak histograms

I am analysing a bunch of data files which represent responsiveness of cells to addition of a drug. If a drug is not added, cell responds normally, if it is added, it shows abnormal patterns: , . We ...
2answers
72 views

### Determining if a time series is random

An example time series would be the stock market, which is sometimes described as a random walk. Over time, this is clearly not the case as it has essentially gone in one direction (up) with only ...
1answer
39 views

### What variance threshold to consider in feature selection?

Consider a numerical dataset with continuous variables, that has been scaled to end up with values in the [0,1] range. How can I compute a reasonable variance threshold for all the variables?
0answers
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### Evaluation of regression models with different evaluations (MSE, variance, VAF etc.)

When comparing several regression models in terms of quality, it seems like most have agreed on the MSE. There are also papers comparing "variance" and "variance accounted for (VAF)". However, there ...
1answer
21 views

### How is the property in eq 15 obtained for Xavier initialization

I am new in this field so please be gentle with terminology. In the original paper; "Understanding the difficulty of training deep feedforward neural networks", I dont understand how equation 15 is ...
0answers
412 views

### How to sort tensor along two axis by variance in TensorFlow?

I have a function that visualizes 2D convolutional kernels. The weights come as 4D-tensors [filter_height, filter_width, in_channels, out_channels], as specified for conv2d. Now I try to sort the ...
1answer
3k views

### How to decide what threshold to use for removing low-variance features?

How to decide what threshold to use for removing low-variance features? Particularly, I have 100000 features and the variances look like: Could I e.g. take the average and use it to split this to ~...
2answers
95 views

### Trade off between Bias and Variance [closed]

What are the best ideas or approaches to trade off between bias and variance in Machine Learning models.
1answer
505 views

### Question on bias-variance tradeoff and means of optimization

So I was wondering how does one, for example, can best optimize the model they are trying to build when confronted with issues presented by high bias or high variance. Now, of course, you can play ...
1answer
55 views

### very low variance explained after applying pca

I applied PCA on MNIST data and found that the first 64 components are able to retain 86% of variance. Is there any problem while applying pca to a big dataset like MNIST. Because in most of the ...
3answers
4k views

### Overfitting Naive Bayes

My question is what are potential reasons for Naive Bayes to perform well on a train set but poorly on a test set? I am working with a variation of the 20news dataset. The dataset has documents, ...
1answer
39 views

### Bootstrapping or Randomly Dividing Dataset to reduce variance?

If I have 10,000 training samples then what should I do: Bootstrapping and train 10 classifiers on it and then aggregating Or randomly divide the dataset into 10 parts and train 10 classifiers on ...
2answers
127 views

### How can I calculate mean and variance incrementally?

Say I have a set S of values, and want to store in a database some summary information about that set, so that later when I acquire a new value v I can make a reasonable estimate of what the summary ...