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Changelog History
Page 6

  • v0.12.8 Changes

    July 15, 2019
    • 🛠 Fix bug that fails to build and install on Windows again. Fix extconf to add Numo::NArray libraries to $lib.

  • v0.12.7 Changes

    July 14, 2019
    • 🛠 Fix bug that fails to build and install on Windows. Add search for Numo::NArray static library path to extconf.

  • v0.12.6 Changes

    July 13, 2019
    • 🛠 Fix extension codes of decision tree classifier and gradient tree regressor for using Numo::NArray.

  • v0.12.5 Changes

    July 02, 2019
    • 🛠 Fix random number generator initialization on gradient boosting estimators to obtain the same result with and without parallel option.

  • v0.12.4 Changes

    June 29, 2019
    • ➕ Add class for multidimensional scaling.
    • 🛠 Fix parameter description on artificial dataset generation method.

  • v0.12.3 Changes

    June 22, 2019
    • ➕ Add class for Power Iteration clustering.
    • ➕ Add classes for artificial dataset generation.

  • v0.12.2 Changes

    June 15, 2019
    • ➕ Add class for cluster analysis with Gaussian Mixture Model.
    • ➕ Add encoder class for categorical features.

  • v0.12.1 Changes

    June 08, 2019
    • 🔨 Refactor kernel support vector classifier.
    • 🔨 Refactor random sampling on tree estimators.

  • v0.12.0 Changes

    June 01, 2019

    💥 Breaking changes

    • For reproductivity, Rumale changes to not repeatedly use the same random number generator in the same estimator. In the training phase, estimators use a copy of the random number generator created in the initialize method. Even with the same algorithm and the same data, the order of random number generation may make slight differences in learning results. By this change, even if the fit method is executed multiple times, the same learning result can be obtained if the same data is given.
    svc = Rumale::LinearModel::SVC.new(random_seed: 0)
svc.fit(x, y)
a = svc.weight_vec
svc.fit(x, y)
b = svc.weight_vec
err = ((a - b)**2).mean

  • v0.11.0 Changes

    • Introduce Parallel gem to improve execution speed for one-vs-the-rest and bagging methods.
    • ➕ Add the n_jobs parameter that specifies the number of jobs for parallel processing in some estimators belong to the Rumale::LinearModel, Rumale::PolynomialModel, and Rumale::Ensemble.
    • 👷 The n_jobs parameter is valid only when parallel gem is loaded.
    require 'rumale'
require 'parallel'

svc = Rumale::LinearModel::SVC.new(n_jobs: -1)