# Tagged Questions

35 views

### Alignment and comparison of two unimodal and one uniformly distributed datasets

This question is similar to the following question: Normalize 3 irregulary distributed datasets and make their datapoints statistically relevant to each other describes similar problem, but is more ...
85 views

### Linear regression from data that don't represent a function

I have $(x,\ y)$ pairs with a strongly suspected linear correlation. So I want to fit the "best" linear function in order to make predictions for unknown $x$'s. These pairs don't represent a function, ...
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### Sales forecasting

I have weekly sales data for the previous year of short-term foods. I want to forecast sales for the next 30 days. I am able to forecast sales figure for a week. But the problem I am facing is how can ...
139 views

### Normalizing SVM predications to [0,1]

I have trained an linear SVM which takes a pair of objects, computes features and is expected to learn a semantic similarity function between objects(we can say that it predicts whether the two ...
94 views

### What are the most popular domain adaptation methods (for transfer learning)?

I understand supervised and unsupervised learning well, and would be able to identify some 'basic' examples of, for example, supervised classifcation as: SVMs Random Forests Logistic Regression ...
315 views

### How can I transform time series data so I can use simpler techniques for fault prediction?

I know this is primarily a statistics site, so if I am off-topic, please redirect me. I have a system with pumps that sometimes break and need to be replaced. I would like to be able to predict the ...
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### Is the true relation between independent and dependent variables assumed to be a function or a distribution?

In classification and regression tasks, we try to learn from a training data set a function mapping a independent variable $X$ to a dependent variable $Y$. When evaluating the error rate of a ...
Let's say you have a jointly gaussian vector random variable $\mathbf{x}$, with mean $\mathbf{M}$ and covariance $\mathbf{S}$. I now transform each scalar element of $\mathbf{x}$ , say $x_j$, with a ...