#le_features = dio.get_le_features(columns, "train_full")
#extra_features = dio.get_features(columns, type_n, le_features)
#extra_valid_features = dio.get_features(columns, type_v, le_features)
#features = dio.join_features("%s_" + type_n + "_count_vector_matrix_max_f_200",
#["Title", "FullDescription", "LocationRaw"],
#extra_features)
#validation_features = dio.join_features("%s_" + type_v + "_count_vector_matrix_max_f_200",
#["Title", "FullDescription", "LocationRaw"],
#extra_valid_features).astype(np.int64)
short_id = "tfidf_200f_l2"
dio.make_counts(vectorizer, short_id, tfidf_columns, type_n, type_v)
extra_features = []
extra_valid_features = []
features = dio.join_features("%s_" + type_n + "_" + short_id + "_matrix",
tfidf_columns,
extra_features)
validation_features = dio.join_features("%s_" + type_v + "_" + short_id + "_matrix",
tfidf_columns,
extra_valid_features)
print features.max()
print features.min()
salaries = dio.get_salaries(type_n, log=False).astype(np.int64)
if not submission:
valid_salaries = dio.get_salaries(type_v, log=False)
def encode_salaries(salaries, bins):
bin_edges = np.linspace(11500.0, 100000, bins + 1, endpoint=True)
#hist, bin_edges = np.histogram(salaries, bins)
print np.diff(bin_edges)
dio = DataIO("Settings.json")
vectorizer = TfidfVectorizer(max_features=200,
norm='l1',
smooth_idf=True,
sublinear_tf=False,
use_idf=True)
short_id = "tfidf_200f_l1"
type_n = "train"
type_v = "valid"
dio.make_counts(vectorizer, short_id, tfidf_columns, "train", "valid")
columns = ["Category", "ContractTime", "ContractType"]
le_features = dio.get_le_features(columns, "train_full")
extra_features = dio.get_features(columns, type_n, le_features)
extra_valid_features = dio.get_features(columns, type_v, le_features)
features = dio.join_features("%s_" + type_n + "_" + short_id + "_matrix",
tfidf_columns, extra_features)
validation_features = dio.join_features(
"%s_" + type_v + "_" + short_id + "_matrix", tfidf_columns,
extra_valid_features)
print features.shape
print validation_features.shape
run = raw_input("OK (Y/N)?")
print run
if run != "Y":
os.exit()
files = joblib.dump(features,
"train_200f_noNorm_categoryTimeType_tfidfl1_features_jl",
compress=9)
files1 = joblib.dump(
