# Questions tagged [variance]

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### Analysis of Variance of different groups

Im working with the following dataset: ...
1 vote
18 views

### Whether to use LDA or QDA

I'm trying to determine whether it's best to use linear or quadratic discriminant analysis for an analysis that I'm working on. It's my understanding that one of the motivations for using QDA over LDA ...
18 views

### VIF Vs Mutual Info

I was searching for the best ways for feature selection in a regression problem & came across a post suggesting mutual info for regression, I tried the same on boston data set. The results were as ...
1 vote
51 views

### Why and how Variational Inference underestimates variance?

I referred to the Quora link here as well, but could not understand clearly. Can anyone please help me understand why and how variational inference underestimates the variance of the true posterior ...
1 vote
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### Do these values of bias and variance make sense?

I have this code: ...
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### How to define the features that bring more variance?

I have a dataset with 10 column, that are my features, and 1732 row that are my registrations. This registration are divided in 15 classes, so I have several registration for every class in my dataset....
1 vote
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### How does bias and variance relate with the training/testing error in Machine Learning. In layman terms does high variance means high testing error

What causes high BIAS/VARIANCE and what are the consequences. Can some one explain in simple terms w.r.t to training/testing errors . Thanks
1 vote
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### SKLearn PCA explained_variance_ration cumsum gives array of 1

I have a problem with PCA. I read that PCA needs clean numeric values. I started my analysis with a dataset called trainDf with shape ...
50 views

### PCA in Tensorflow

I am currently trying to understand the code of PCA in TensorFlow Extended. I tried to understand how the Covariance Matrix is calculated once we have a PCollection (Beam). I wanted to execute the ...
21 views

### Relationship of Bias and size of dataset

I was reading the following book: http://www.feat.engineering/resampling.html where the author mentioned the below: Generally speaking, as the amount of data in the analysis set shrinks, the ...
72 views

### Evaluating if metric of one group is higher than the metric of another group when group sizes differ significantly

I am working with a dataset that contains data of applicant income, gender, and loan status (whether or not the person was approved for a loan). I've created the following plots from the data. The ...
34 views

### learning curves of a classification algorithm

I a trying to understand this learning curve of a classification problem. But I am not sure what to infer. I believe that I have overfitting but I cannot sure. Very low training loss that’s very ...
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### Ideas to enforce uniformity of error in linear models

I am looking for ideas to not only solve the least square problem, but to enforce errors to be roughly similar. One idea I had is to add the variance of errors in the classical Ordinary Least Square ...
1 vote
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### Repeating values caught with a binary classifier

If my machine is broken, it starts to repeat certain channels. Thing is if there are no out-liars, it is difficult to tell it's broken as we would expect all data points to be around the same value. I ...
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### Subtraction of two variances (scores)

I was wondering, would it be correct to say, when we treat two variances of two populations as a random variable itself (or as a score), that we can simply get a resultant variance V_subtract = V_pop1 ...
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### Query regarding variance smoothing in Naive Bayes classification

var_smoothing: float, default=1e-9 --> Portion of the largest variance of all features that is added to variances for calculation stability. Source: https://scikit-learn.org/stable/modules/...
83 views

### Does Bias always decrease when Complexity increase?

(I'm just starting learning about ML stuff and so please don't be rude if the following question is to stupid or totally wrong) I'm reading about Bias-Variance Trade off and I don't understand the (...
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### I am not sure whether I am being asked to calculate the variance or the irreducible error

The question: Suppose we randomly sample a training set D from some unknown distribution. For each training set D we sample, we train a regression model to predict $y$ from $x$. We repeat this 10 ...
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### Sampling a data based on average and variance of another data

I have a set of textual datasets that have the following average and variance tokens lengths: ...
1 vote
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### Checking my understanding of the bias-variance tradeoff

Hello fellow DS aficionados, I'm trying to clarify some confusing feedback I got from a homework problem. We were told to recreate the bias-variance tradeoff graph using the first graph below as an ...
1 vote
19 views

### How can I calculate the level of agreement between my K-Means cluster labels and my ground truth labels in R?

I have made a K-Means clustering from 3 rasters with various values of k (k=2, k=4, k=7) and would like to know which values of k explains the most variance in my ground-truth data or the value of k ...
22 views

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### derivation for expected value for variance

Hi Im taking a course about probability distribution in datascience and below is derivation of the expected value for the variance Variance = expected value of the squared difference from mean for ...
24 views

### mean and variance of a dataset

I have a simple question. Please see the below screenshot : It is from a midterm exam from a university : https://cedar.buffalo.edu/~srihari/CSE555/exams/midterm-solution-2006.pdf My questions is how ...
125 views

### Figure out relative importance of entity attributes

I'm trying to understand how various aspects of a movie contribute to its gross revenue. I want to rank a movie's attributes in that sense - the attributes that most strongly determine the revenue are ...
1 vote
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### KNN with high-variance data [closed]

KNN doesn't work well with high-variance data, so how should I fit my data? Here is an example of what the data looks like:
1 vote
106 views

### Levene test for equal variance

I would like to run one-way ANOVA test on my data. I saw that one of several assumptions for one-way ANOVA is that there needs to be homogeneity of variances. I have run the test for different data-...
484 views

### Elimination of features based on high covariance without affecting performance?

I ran into a question where the answer ran me into a big doubt. Suppose we have a dataset $A=${$x1,x2,y$} in which $x1$ and $x2$ are our features and $y$ is the label. Also, suppose that the ...
1 vote
53 views

### Model Selection using Bias Variance Trade Off

I have a Regression Model with Train MAPE as 6% and Test MAPE as 15%. This appears to me as a clear case of over fitting. But can I still use this model assuming 15% Error is not a bad number after-...
1 vote
193 views

### PCA, covariance, eigenvector matrix and rotation [closed]

I am following the Coursera NLP specialization, and in particular the lab "Another explanation about PCA" in Course 1 Week 3. From the lab, I recovered the following code. It creates 2 ...
1 vote
26 views

### Is there a quantitative way to determine if a class of algorithms tends produce low bias or low variance models?

I understand that some machine learning models tend to be low bias, whereas others tend to be low variance (source). As an example, a linear regression will tend to have low variance error and high ...
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### How can I compute the ideal variance threshold value for my data?

I have a dataset that contains n features scaled between [0,1]. I would use an unsupervised feature selection algorithm (variance thresholding). How can I compute the threshold value?
1 vote
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### Confidence interval for class membership probabilities

I would like to calculate confidence intervals for predicted probabilities of a class membership obtained with randomForest. I know I could use predict.all in randomForest(), which gives me the ...
1 vote
50 views

### Find inputs that give highest variance in output space

I have a relatively simple problem that I think should have a known solution, but that I can't figure out. Any help would be greatly appreciated. Basically, I have a function \$f : \mathbb{R}^d \...