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🎨 Fix default value of max_iter on LinearModel estimators
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@yoshoku
yoshoku committed Oct 2, 2020
1 parent 89c6abe commit 63e71df
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Showing 8 changed files with 15 additions and 15 deletions.
2 changes: 1 addition & 1 deletion lib/rumale/linear_model/base_sgd.rb
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Expand Up @@ -171,7 +171,7 @@ def initialize
@params[:fit_bias] = true
@params[:reg_param] = 0.0
@params[:l1_ratio] = 0.0
@params[:max_iter] = 200
@params[:max_iter] = 1000
@params[:batch_size] = 50
@params[:tol] = 0.0001
@params[:verbose] = false
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4 changes: 2 additions & 2 deletions lib/rumale/linear_model/elastic_net.rb
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Expand Up @@ -10,7 +10,7 @@ module LinearModel
#
# @example
# estimator =
# Rumale::LinearModel::ElasticNet.new(reg_param: 0.1, l1_ratio: 0.5, max_iter: 200, batch_size: 50, random_seed: 1)
# Rumale::LinearModel::ElasticNet.new(reg_param: 0.1, l1_ratio: 0.5, max_iter: 1000, batch_size: 50, random_seed: 1)
# estimator.fit(training_samples, traininig_values)
# results = estimator.predict(testing_samples)
#
Expand Down Expand Up @@ -59,7 +59,7 @@ class ElasticNet < BaseSGD
# @param random_seed [Integer] The seed value using to initialize the random generator.
def initialize(learning_rate: 0.01, decay: nil, momentum: 0.9,
reg_param: 1.0, l1_ratio: 0.5, fit_bias: true, bias_scale: 1.0,
max_iter: 200, batch_size: 50, tol: 1e-4,
max_iter: 1000, batch_size: 50, tol: 1e-4,
n_jobs: nil, verbose: false, random_seed: nil)
check_params_numeric(learning_rate: learning_rate, momentum: momentum,
reg_param: reg_param, l1_ratio: l1_ratio, bias_scale: bias_scale,
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4 changes: 2 additions & 2 deletions lib/rumale/linear_model/lasso.rb
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Expand Up @@ -10,7 +10,7 @@ module LinearModel
#
# @example
# estimator =
# Rumale::LinearModel::Lasso.new(reg_param: 0.1, max_iter: 500, batch_size: 20, random_seed: 1)
# Rumale::LinearModel::Lasso.new(reg_param: 0.1, max_iter: 1000, batch_size: 20, random_seed: 1)
# estimator.fit(training_samples, traininig_values)
# results = estimator.predict(testing_samples)
#
Expand Down Expand Up @@ -55,7 +55,7 @@ class Lasso < BaseSGD
# @param random_seed [Integer] The seed value using to initialize the random generator.
def initialize(learning_rate: 0.01, decay: nil, momentum: 0.9,
reg_param: 1.0, fit_bias: true, bias_scale: 1.0,
max_iter: 200, batch_size: 50, tol: 1e-4,
max_iter: 1000, batch_size: 50, tol: 1e-4,
n_jobs: nil, verbose: false, random_seed: nil)
check_params_numeric(learning_rate: learning_rate, momentum: momentum,
reg_param: reg_param, bias_scale: bias_scale,
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4 changes: 2 additions & 2 deletions lib/rumale/linear_model/linear_regression.rb
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Expand Up @@ -10,7 +10,7 @@ module LinearModel
#
# @example
# estimator =
# Rumale::LinearModel::LinearRegression.new(max_iter: 500, batch_size: 20, random_seed: 1)
# Rumale::LinearModel::LinearRegression.new(max_iter: 1000, batch_size: 20, random_seed: 1)
# estimator.fit(training_samples, traininig_values)
# results = estimator.predict(testing_samples)
#
Expand Down Expand Up @@ -68,7 +68,7 @@ class LinearRegression < BaseSGD
# If solver = 'svd', this parameter is ignored.
# @param random_seed [Integer] The seed value using to initialize the random generator.
def initialize(learning_rate: 0.01, decay: nil, momentum: 0.9,
fit_bias: true, bias_scale: 1.0, max_iter: 200, batch_size: 50, tol: 1e-4,
fit_bias: true, bias_scale: 1.0, max_iter: 1000, batch_size: 50, tol: 1e-4,
solver: 'auto',
n_jobs: nil, verbose: false, random_seed: nil)
check_params_numeric(learning_rate: learning_rate, momentum: momentum,
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4 changes: 2 additions & 2 deletions lib/rumale/linear_model/logistic_regression.rb
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Expand Up @@ -15,7 +15,7 @@ module LinearModel
#
# @example
# estimator =
# Rumale::LinearModel::LogisticRegression.new(reg_param: 1.0, max_iter: 200, batch_size: 50, random_seed: 1)
# Rumale::LinearModel::LogisticRegression.new(reg_param: 1.0, max_iter: 1000, batch_size: 50, random_seed: 1)
# estimator.fit(training_samples, traininig_labels)
# results = estimator.predict(testing_samples)
#
Expand Down Expand Up @@ -72,7 +72,7 @@ class LogisticRegression < BaseSGD
def initialize(learning_rate: 0.01, decay: nil, momentum: 0.9,
penalty: 'l2', reg_param: 1.0, l1_ratio: 0.5,
fit_bias: true, bias_scale: 1.0,
max_iter: 200, batch_size: 50, tol: 1e-4,
max_iter: 1000, batch_size: 50, tol: 1e-4,
n_jobs: nil, verbose: false, random_seed: nil)
check_params_numeric(learning_rate: learning_rate, momentum: momentum,
reg_param: reg_param, l1_ratio: l1_ratio, bias_scale: bias_scale,
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4 changes: 2 additions & 2 deletions lib/rumale/linear_model/ridge.rb
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ module LinearModel
#
# @example
# estimator =
# Rumale::LinearModel::Ridge.new(reg_param: 0.1, max_iter: 500, batch_size: 20, random_seed: 1)
# Rumale::LinearModel::Ridge.new(reg_param: 0.1, max_iter: 1000, batch_size: 20, random_seed: 1)
# estimator.fit(training_samples, traininig_values)
# results = estimator.predict(testing_samples)
#
Expand Down Expand Up @@ -70,7 +70,7 @@ class Ridge < BaseSGD
# @param random_seed [Integer] The seed value using to initialize the random generator.
def initialize(learning_rate: 0.01, decay: nil, momentum: 0.9,
reg_param: 1.0, fit_bias: true, bias_scale: 1.0,
max_iter: 200, batch_size: 50, tol: 1e-4,
max_iter: 1000, batch_size: 50, tol: 1e-4,
solver: 'auto',
n_jobs: nil, verbose: false, random_seed: nil)
check_params_numeric(learning_rate: learning_rate, momentum: momentum,
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4 changes: 2 additions & 2 deletions lib/rumale/linear_model/svc.rb
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ module LinearModel
#
# @example
# estimator =
# Rumale::LinearModel::SVC.new(reg_param: 1.0, max_iter: 200, batch_size: 50, random_seed: 1)
# Rumale::LinearModel::SVC.new(reg_param: 1.0, max_iter: 1000, batch_size: 50, random_seed: 1)
# estimator.fit(training_samples, traininig_labels)
# results = estimator.predict(testing_samples)
#
Expand Down Expand Up @@ -74,7 +74,7 @@ class SVC < BaseSGD
def initialize(learning_rate: 0.01, decay: nil, momentum: 0.9,
penalty: 'l2', reg_param: 1.0, l1_ratio: 0.5,
fit_bias: true, bias_scale: 1.0,
max_iter: 200, batch_size: 50, tol: 1e-4,
max_iter: 1000, batch_size: 50, tol: 1e-4,
probability: false,
n_jobs: nil, verbose: false, random_seed: nil)
check_params_numeric(learning_rate: learning_rate, momentum: momentum,
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4 changes: 2 additions & 2 deletions lib/rumale/linear_model/svr.rb
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ module LinearModel
#
# @example
# estimator =
# Rumale::LinearModel::SVR.new(reg_param: 1.0, epsilon: 0.1, max_iter: 200, batch_size: 50, random_seed: 1)
# Rumale::LinearModel::SVR.new(reg_param: 1.0, epsilon: 0.1, max_iter: 1000, batch_size: 50, random_seed: 1)
# estimator.fit(training_samples, traininig_target_values)
# results = estimator.predict(testing_samples)
#
Expand Down Expand Up @@ -68,7 +68,7 @@ def initialize(learning_rate: 0.01, decay: nil, momentum: 0.9,
penalty: 'l2', reg_param: 1.0, l1_ratio: 0.5,
fit_bias: true, bias_scale: 1.0,
epsilon: 0.1,
max_iter: 200, batch_size: 50, tol: 1e-4,
max_iter: 1000, batch_size: 50, tol: 1e-4,
n_jobs: nil, verbose: false, random_seed: nil)
check_params_numeric(learning_rate: learning_rate, momentum: momentum,
reg_param: reg_param, bias_scale: bias_scale, epsilon: epsilon,
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