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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_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.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.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.mm
1"> <node TEXT="Lorem ipsum. (ロ...raw.githubusercontent.com/codelibs/fess-testdata/master/xml/test.mm -
test.h
// 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.h -
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 -
ensemble.rst.txt
mean_squared_error(y_test, est.predict(X_test)) 5.00... >>> _ = est.set_pa...to est >>> mean_squared_error(y_test, est.predict(X_test)) 3.84......scikit-learn.org/stable/_sources/modules/ensemble.rst.txt -
install.rst.txt
running the full scikit-learn test suite via automated continuous...ckages\\sklearn\\datasets\\tests\\data\\openml\\292\\api-v1-...scikit-learn.org/stable/_sources/install.rst.txt -
neighbors.rst.txt
X_test, y_train, y_test = train_test_split(X, y, ......>>> print(nca_pipe.score(X_test, y_test)) 0.96190476... .. |nca_classification_1|...scikit-learn.org/stable/_sources/modules/neighbors.rst.txt