weight
Version, currently master branch1 version
- master branchlatestNov 18, 2021
github.com/drujensen/weight
example linear regression using SHAInet
3 stars
0 dependents
License: MIT
Installation
# Add this to your shard.yml
dependencies:
weight:
github: drujensen/weight
branch: mastermaster is a branch, not a release, so this tracks it rather than pinning a version.
Then run:
shards installshard.yml
- Crystal
0.24.2- License
- MIT
- Author
- Dru Jensen
- Target
weightfrom src/weight.cr
Dependencies
Runtime Dependencies
- evolvenet*github: drujensen/evolvenet, branch: master
README
weight
Example SHAInet model to perform linear regression using Height/Weight.
Below is a Keras equivalent model:
import pandas as pd
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import SGD
df = pd.read_csv('./data/weight-height.csv')
X = df[['Height']].values
Y = df['Weight'].values
model = Sequential()
model.add(Dense(1, input_shape=(1,)))
model.compile(SGD(lr=0.01), 'mean_squared_error')
model.fit(X, Y, epochs=40)
model.predict([75])
Installation
Requires Crystal 0.24.2
Usage
crystal src/weight.cr
Development
Experimenting with different models. Currently Adam is failing with NaN errors. SGDM seems to provide fairly accurate results.
Contributing
- Fork it ( https://github.com/drujensen/weight/fork )
- Create your feature branch (git checkout -b my-new-feature)
- Commit your changes (git commit -am 'Add some feature')
- Push to the branch (git push origin my-new-feature)
- Create a new Pull Request
Contributors
- drujensen Dru Jensen - creator, maintainer
Documentation
Built from the current release. The first visit to a release nobody has asked for starts its build.
Links
This branch
- Branch
master- Seen
- Nov 18, 2021
- Crystal
0.24.2- Indexed
- yes
Dependents
No indexed shard depends on this one yet.
Repository
github.com/drujensen/weight
Metadata
- Created
- Aug 12, 2026
- Updated
- Aug 14, 2026
- Synced
- Aug 14, 2026
- Versions
- 1