Questions tagged [variance]

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Learning curve using micro F-score and macro F-score

I plotted the learning curves using micro and macro F-scores for a Multinomial Naive Bayes classifier. The first plot is made using micro F-score, and the second using macro F-score. I find it quite ...
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22 views

Measure of variety within list/cluster

I have a dataset of about 53000 points. It has been clustered twice, based on two sets of unrelated attributes. For the first clustering (clustering 1) I used DBScan, and it ended up with about 700 ...
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14 views

Sampling trying to keep as much multivariate variance as possible

We can use PCA for dimensionality reduction, but at the cost of getting "uninterpretable" variables. I was thinking if anyone considered a sampling technique that would try to aim keeping as much of ...
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14 views

Identify appropriate variance stabilization transform

I have a heavy tailed data which is heteroscedastic in nature. I need to apply some ML algorithms on this data that are good for normal distribution. So I want to transform the data. I tried Box cox ...
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1answer
62 views

bias variance decomposition for classification problem

It is given that: MSE = bias$^2$ + variance I can see the mathematical relationship between MSE, bias, and variance. However, how do we understand the mathematical intuition of bias and variance for ...
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0answers
52 views

Math behind, MSE = bias^2 + variance

Based on the deeplearningbook: $$MSE = E[(\theta_m^{-} - \theta)^2]$$ $$equals$$ $$Bias(\theta_m^{-})^2 + Var(\theta_m^{-})$$ where m is the number of samples ...
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0answers
18 views

F-test for comparing the mean of two groups

What would be the procedure, in terms of F-test, if I would like to check if the mean of one group is greater than the other group (alternative hypothesis: $\mu_1 > \mu_2$)? And also what would ...
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10 views

Would it make technical sense to model its two known subelements separately (CLV example)?

Let's assume Customer Lifetime Value (CLV) is defined as average basket x frequency. Option A is to build model predicting CLV ...
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0answers
94 views

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 ...
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396 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 ...
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1answer
74 views

Convert a pdf into a conditional pdf such that mean increases and std dev falls

Let success metric(for some business use case I am working on) be a continuous random variable S. The mean of pdf defined on S indicates the chance of success. Higher the mean more is the chance of ...
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1answer
28 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?
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11 views

Evaluating randomness in a model performance

I'm evaluating the variability in performance (AUC) in the test set of a machine learning model with an intrinsic random component (xgboost). How many sources of variation should I use? Just ...
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1answer
51 views

Implication of a dominant Principal Component in PCA analysis

I need help, are there any practical implications of a dominant principal component. For example, if of three PCs, PC1 explains almost 100% of the variance in this dataset, What does this mean in ...
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1answer
26 views

Bias and variance in the model o in the predictions?

This topic confuses me. In the literature or articles, when talking about bias and variance in automatic learning, specifically in cross-validation, do they refer to the high bias (underfitting) and ...
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19 views

ZCA: Covariance of Large Image Database

I have an overall question if my method is sound, so please bear with me in this description :). I have a large image database and I wanted to create a preprocessing step using ZCA. The issue is that ...
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7 views

Two tailed F test, correct rejection of the null hypothesis

I am performing an F test for equality of two variances by following this website formula https://itl.nist.gov/div898/handbook/eda/section3/eda359.htm, however it states that In the above formulas ...
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4 views

What are some common sources of variance in a convolutional neural network DICE scores?

I know it's basically impossible to pinpoint the exact answer to this question without data, code, architecture, etc, but I'm curious as to if anyone has any general ideas on why this might be ...
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64 views

Finding unaffected data in a dataset

The data set has missing values. Further examination tells that they are spread along 1.5 standard deviation from the median with distribution mean = 0 & variance = 5. How much data (in percentage)...
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1answer
45 views

Initialisation methods and variance

I'm trying to understand some weights initialisation methods by reading the article http://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf . But I don't understand their notation on variance. Right ...