Questions tagged [supervised-learning]

Supervised learning is a type of machine learning algorithm that learns a mapping function y = f(x) between input variables (x) and output variables (y). The two most common supervised learning tasks are classification and regression.

Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal).

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difference between supervised learning and imitation learning

I find these two concepts confusing because I feel that imitation learning is just a 'subset' of supervised learning. But after thinking hard enough, I could not think of any difference and feel that they are the same. Are they the same? or…
cgo
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regarding the inclusion of missclassified data in final training

I find it best to ask my question in terms of cross-validation. Here it goes: Suppose a binary classification problem, for which cross-validation has been applied for a certain learning algorithm. Let's say that both the CV train error and CV test…
Enk9456
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Definition of weak and strong learners

What is the exact definition, or at least the main idea, of weak and strong learners? For instance, these terms are used in propositions such as "Boosting is based on weak learners". Regarding the viewpoint that weak learners are of the type…
Enk9456
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What algorithm to use

I am stuck on what algorithm to use. I want to train my program on a dataset where i have an input image, and an output image which is a modified version of the input. The whole context of the image is important, and each pixel counts. After…
Martin M
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How to train a classification algorithm with multiple samples that represent the class?

Hopefully explaining this is the right way. Apologies if some of it is unclear at all. I am working with network data and want to use a supervised approach to identify whether a sample (packet) is malicious or not, so a binary classification. In my…
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Compare job ads with a given set of categories (which each consists of terms)

For a recent research paper, I plan to perform the following, for which I'd kindly ask for your advice. I obtained a set of a few thousand job ads. I now want to analyse how and whether these job ads include 'content' that has been previously…
Spooz
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Which algorithm should I use for this use cases?

I got data like: Student age Student study subject Student gender Student academic result Student joined actives and I got the student graduation income. So, I would like to train a model, so that I can guest a student with some background and…