https://github.com/drsoliddevil/mlr-gd

Multiple linear regression by gradient descent.

https://github.com/drsoliddevil/mlr-gd

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

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  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (11.2%) to scientific vocabulary

Keywords

data-science gradient-descent linear-regression machine-learning ml numpy python regression
Last synced: 5 months ago · JSON representation

Repository

Multiple linear regression by gradient descent.

Basic Info
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 4
Topics
data-science gradient-descent linear-regression machine-learning ml numpy python regression
Created about 1 year ago · Last pushed 10 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Security

README.md




GitHub Release PyPI - Downloads PyPI - Python Version GitHub repo size Read the Docs GitHub License


Multiple linear regression by gradient descent.

Installation

To install mlr-gd you can use pip:

bash $ python -m pip install mlr-gd

Alternatively, you can install it by cloning the GitHub repository: bash $ git clone https://github.com/DrSolidDevil/mlr-gd.git $ cd mlr-gd $ pip install .


To import the package into your script:
python import melar



Example

```python import numpy as np import melar

y = x1 + 0.5*x2

x = np.array([[1, 3, 5, 8], [1, 2, 3, 6]]) y = np.array([1.5, 4, 6.5, 11])

learning_rate = 0.01 generations = 100

model = melar.LinearRegression(weightsamount=2) model.train(x, y, learningrate, generations, do_print=True) print(f"Weights: {model.weights}, Bias: {model.bias}") ```

Gen: 0, Cost: 95.4852602406095 Gen: 1, Cost: 5.593624864417041 Gen: 2, Cost: 0.3286224504551768 Gen: 3, Cost: 0.020244781001893267 ... Gen: 99, Cost: 0.0007438760098695897 Training Complete Weights: [0.94643617 0.57630021], Bias: -0.003265101149422934

Owner

  • Login: DrSolidDevil
  • Kind: user

Disabled

GitHub Events

Total
  • Create event: 37
  • Commit comment event: 1
  • Issues event: 7
  • Release event: 4
  • Watch event: 2
  • Delete event: 28
  • Issue comment event: 8
  • Push event: 132
  • Pull request review event: 2
  • Pull request event: 47
  • Fork event: 1
Last Year
  • Create event: 37
  • Commit comment event: 1
  • Issues event: 7
  • Release event: 4
  • Watch event: 2
  • Delete event: 28
  • Issue comment event: 8
  • Push event: 132
  • Pull request review event: 2
  • Pull request event: 47
  • Fork event: 1

Committers

Last synced: 10 months ago

All Time
  • Total Commits: 186
  • Total Committers: 3
  • Avg Commits per committer: 62.0
  • Development Distribution Score (DDS): 0.473
Past Year
  • Commits: 186
  • Committers: 3
  • Avg Commits per committer: 62.0
  • Development Distribution Score (DDS): 0.473
Top Committers
Name Email Commits
DrSolidDevil 5****l 98
DrSolidDevil 5****l 75
RedDingleBerry 1****y 13

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 4
  • Total pull requests: 50
  • Average time to close issues: about 6 hours
  • Average time to close pull requests: 30 minutes
  • Total issue authors: 1
  • Total pull request authors: 2
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.02
  • Merged pull requests: 42
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 4
  • Pull requests: 50
  • Average time to close issues: about 6 hours
  • Average time to close pull requests: 30 minutes
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.02
  • Merged pull requests: 42
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • DrSolidDevil (4)
Pull Request Authors
  • DrSolidDevil (42)
  • RedDingleBerry (8)
Top Labels
Issue Labels
documentation (2) bug (1) enhancement (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 40 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 7
  • Total maintainers: 1
pypi.org: mlr-gd

A package for multiple linear regression by gradient descent.

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 40 Last month
Rankings
Dependent packages count: 9.8%
Average: 32.4%
Dependent repos count: 55.0%
Maintainers (1)
Last synced: 6 months ago