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test_nocharset.html
Lorem ipsum. (ロレム・イプサム) 吾輩は猫である。raw.githubusercontent.com/codelibs/fess-testdata/master/html/test_nocharset.html -
test.cpp
#include <sdtio.h> int main(void) { printf("Lorem ipsum. (ロレム・イプサム) 吾輩は猫である。"); }raw.githubusercontent.com/codelibs/fess-testdata/master/source_code/test.cpp -
test.mm
1"> <node TEXT="Lorem ipsum. (ロ...raw.githubusercontent.com/codelibs/fess-testdata/master/xml/test.mm -
test.js
function foo() { var bar = "Lorem ipsum. (ロレム・イプサム) 吾輩は猫である。"; }raw.githubusercontent.com/codelibs/fess-testdata/master/source_code/test.js -
test.java
test.javapackage com.foo.bar; public class Test { public String...String test="Lorem ipsum. (ロレム・イプサム) 吾輩は猫である。"; } 5...raw.githubusercontent.com/codelibs/fess-testdata/master/source_code/test.java -
test.hpp
// Lorem ipsum. (ロレム・イプサム) 吾輩は猫である。 typedef int & Integer;raw.githubusercontent.com/codelibs/fess-testdata/master/source_code/test.hpp -
plot_multi_metric_evaluation.rst.txt
1)[0][0] best_score = results["mean_test_%s" % scorer][best_index]...etc...) The ``best_estimator_``, ``best_index_``, ``best_score_``...scikit-learn.org/stable/_sources/auto_examples/model_selection/plot_multi_metric_evaluation.rst.txt -
cross_validation.rst.txt
available data as a **test set** ``X_test, y_test``. Note that the...>>> X_train, X_test, y_train, y_test = train_test_split( ... X,...scikit-learn.org/stable/_sources/modules/cross_validation.rst.txt -
feature_selection.rst.txt
the best features based on univariate statistical tests. It can...we can use a F-test to retrieve the two best features for a dataset...scikit-learn.org/stable/_sources/modules/feature_selection.rst.txt -
model_evaluation.rst.txt
ratio (pre-test and post-tests): .. math:: \text{post-test odds} =...\frac{\text{pre-test probability}}{1 - \text{pre-test probability}},...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt