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src/s/o/solutions-HEAD/kaggle/insults/amueller/train.py   solutions(Download)
 
 
from util import load_data, load_extended_data, write_test, load_test
 
from IPython.core.debugger import Tracer
def grid_search():
    comments, labels = load_data()
    param_grid = dict(logr__C=np.arange(1, 20, 5))
    clf = build_nltk_model()
 
def analyze_output():
    comments, labels = load_data()
    y_train, y_test, comments_train, comments_test = \
            train_test_split(labels, comments, random_state=1)
    #from sklearn.tree import DecisionTreeClassifier

src/k/a/kaggle_insults-HEAD/train.py   kaggle_insults(Download)
 
 
from util import load_data, load_extended_data, write_test, load_test
 
from IPython.core.debugger import Tracer
def grid_search():
    comments, labels = load_data()
    param_grid = dict(logr__C=np.arange(1, 20, 5))
    clf = build_nltk_model()
 
def analyze_output():
    comments, labels = load_data()
    y_train, y_test, comments_train, comments_test = \
            train_test_split(labels, comments, random_state=1)
    #from sklearn.tree import DecisionTreeClassifier

src/s/o/solutions-HEAD/kaggle/insults/amueller/old.py   solutions(Download)
from sklearn.feature_selection import SelectPercentile, chi2
 
from util import load_data
 
from IPython.core.debugger import Tracer
def jellyfish():
    #import jellyfish
 
    comments, dates, labels = load_data()
    y_train, y_test, comments_train, comments_test = \
def test_stacker():
    comments, dates, labels = load_data()
    clf = LogisticRegression(tol=1e-8, C=0.01, penalty='l2')
    countvect_char = TfidfVectorizer(ngram_range=(1, 5),
            analyzer="char", binary=False)
def bagging():
    from sklearn.feature_selection import SelectPercentile, chi2
 
    comments, dates, labels = load_data()
    select = SelectPercentile(score_func=chi2, percentile=4)

src/k/a/kaggle_insults-HEAD/old.py   kaggle_insults(Download)
from sklearn.feature_selection import SelectPercentile, chi2
 
from util import load_data
 
from IPython.core.debugger import Tracer
def jellyfish():
    #import jellyfish
 
    comments, dates, labels = load_data()
    y_train, y_test, comments_train, comments_test = \
def test_stacker():
    comments, dates, labels = load_data()
    clf = LogisticRegression(tol=1e-8, C=0.01, penalty='l2')
    countvect_char = TfidfVectorizer(ngram_range=(1, 5),
            analyzer="char", binary=False)
def bagging():
    from sklearn.feature_selection import SelectPercentile, chi2
 
    comments, dates, labels = load_data()
    select = SelectPercentile(score_func=chi2, percentile=4)