Questions tagged [learning]

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Comparing Multiple ML Models: Do CV for each model independently, or use same splits for each model?

I was trying to figure out the most efficient way to compare multiple models using sklearn. Let's say I have three models to compare: Naive Bayes Logistic Regression SVM I want to train and obtain ...
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1answer
24 views

Test Accuracy same as Training Accuracy

I am building a prediction model using KNN. After experimenting the data using KFOLD Cross Validation technique, I've got the mean accuracy and applied them on the real model and it turns out that the ...
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1answer
37 views

Empirical Risk Minimization: why is the rate of convergence important?

In section 4 Empirical Risk Minimzation of the paper Principles of Risk Minimization for Learning Theory by V. Vapnik, the author says the following: In order to solve this problem, the following ...
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16 views

Public data and examples for practicing distribution fitting? [closed]

Are there public data for practicing distribution fitting and examples? I want to practice parameter estimation with various methods. To do so it would be helpful if there are reliable examples of ...
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2answers
36 views

Econometrics online learning course [closed]

i would kindly like to ask you for recommendations regarding introductory, but more importantly advanced online econometrics courses (theory as well as applied, preferably in R). I would be most ...
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3answers
103 views

How to conduct linear regression with lots of data?

Say we have an absolutely huge dataset, and it's too much to put it all into one linear regression model to train. How can we go about using all of this data? I was thinking that we could break this ...
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0answers
68 views

Does LSTM provide online learning for streaming data (online parameters' update)?

I read something about LSTM and I noticed that the training is done on a training set and it is long-lasting. How to behave to predict new points if I have daily streaming data? Do I have to train the ...
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0answers
21 views

Normal learning model

How can I go about calculating a posterior with this information? Suppose that $z_{t}$ is a stochastic signal about a variable $\eta$, $z_{t}=-\alpha\eta +\epsilon_{t}$, where $\eta$ is Normally ...
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0answers
35 views

Combining two datasets for Random Forest binary classification

I was tasked to perform a brief meta-analysis between three datasets, all with identical features, that studied different sources of neurodegeneration. As a meta-analysis these datasets were drawn ...
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21 views

Machine learning algorithm for finding most similar entries in dataset

I have a pandas Dataframe, which has data as structured below. ...
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1answer
25 views

Convergence under large set of learning rates

What is the interpretation of a stochastic optimization problem where a gradient descent algorithm is converging under a wide range of learning rate schedules (including ones with quite large initial ...