How can we leverage JavaScript to create logistic regression models for datasets and derive the beta-coefficients?

Question

How can we leverage JavaScript to create logistic regression models for datasets and derive the beta-coefficients?

Exploring Logistic Regression in JavaScript

In my current project, I am looking to fit a multi-variate logistic regression model to a dataset using JavaScript. My main goal is to extract the beta-coefficients for this model. Can anyone provide guidance on how to implement this functionality in JavaScript?

My Attempts So Far

js-regression (npm): I have tried using the logistic regression example from this package, but it appears to focus more on training and classification rather than coefficient extraction.
machinelearn (npm): Although the documentation includes a logistic regression example, I have struggled to make it work. It seems like this package is also geared towards training and classification tasks.

javascript npm logistic-regression

Answer 1

Answer №1

Solution

After spending time with the js-regression library, I went through its source code and realized that I had incorrectly set up the structure of my training data. In essence, the theta attribute of the model generated using the fit() function contains a list of coefficients.

Code

let model = logistic.fit(training_dataset); // Generate the model
console.log(model); // Print out the model

The output was as follows:

{
  theta: [ ... ], // These were the coefficients
  threshold: 1,
  cost: ...,
  config: { alpha: 0.001, lambda: 0, iterations: 10000 }
}

Answer 2

Solution

After spending time with the js-regression library, I went through its source code and realized that I had incorrectly set up the structure of my training data. In essence, the theta attribute of the model generated using the fit() function contains a list of coefficients.

Code

let model = logistic.fit(training_dataset); // Generate the model
console.log(model); // Print out the model

The output was as follows:

{
  theta: [ ... ], // These were the coefficients
  threshold: 1,
  cost: ...,
  config: { alpha: 0.001, lambda: 0, iterations: 10000 }
}

How can we leverage JavaScript to create logistic regression models for datasets and derive the beta-coefficients?

Exploring Logistic Regression in JavaScript

My Attempts So Far

Answer №1

Solution

Code

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