• Home
  • Features
  • Pricing
  • Docs
  • Announcements
  • Sign In

aigamedev / scikit-neuralnetwork / 288 / 1
100%
master: 100%

Build:
DEFAULT BRANCH: master
Ran 13 May 2015 05:38PM UTC
Files 16
Run time 1s
Badge
Embed ▾
README BADGES
x

If you need to use a raster PNG badge, change the '.svg' to '.png' in the link

Markdown

Textile

RDoc

HTML

Rst

13 May 2015 05:31PM UTC coverage: 100.0%. Remained the same
288.1

push

travis-ci

alexjc
Merge pull request #47 from aigamedev/regularize

Regularization support using L1 and L2, not just dropout.  Can be enabled using the following:

````
from sknn.mlp import Regressor, Layer

nn = Regressor(
    layers=[Layer("Rectifier", units=100), Layer("Linear")],
    regularize='L2',
    weight_decay=0.0001,
    n_iter=10)
nn.fit(X_train, y_train)
````

Each layer also takes a weight_decay `parameter` for customized regularization.  Dropout has now become an additional `regularize` option string.

Closes #44.

1092 of 1092 relevant lines covered (100.0%)

1.0 hits per line

Source Files on job 288.1
  • Tree
  • List 0
  • Changed 3
  • Source Changed 3
  • Coverage Changed 3
Coverage ∆ File Lines Relevant Covered Missed Hits/Line
  • Back to Build 288
  • Travis Job 288.1
  • 2e6e1be4 on github
  • Prev Job for on master (#287.1)
  • Next Job for on master (#295.1)
STATUS · Troubleshooting · Open an Issue · Sales · Support · CAREERS · ENTERPRISE · START FREE · SCHEDULE DEMO
ANNOUNCEMENTS · TWITTER · TOS & SLA · Supported CI Services · What's a CI service? · Automated Testing

© 2026 Coveralls, Inc