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gm_strategy_cvr
Commit d4f9db15 authored by 赵威's avatar 赵威
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remove cross field for tractate

parent e31cd2ac
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Showing with 56 additions and 56 deletions
src/models/esmm/fe/tractate_fe.py
View file @ d4f9db15
......@@ -288,20 +288,20 @@ CATEGORICAL_COLUMNS = [
"click_tractate_id5",
"is_related_service",
"service_city",
"device_fd2",
"device_sd2",
"device_fs2",
"device_ss2",
"device_fp2",
"device_sp2",
"device_p2",
"device_fd3",
"device_sd3",
"device_fs3",
"device_ss3",
"device_fp3",
"device_sp3",
"device_p3",
# "device_fd2",
# "device_sd2",
# "device_fs2",
# "device_ss2",
# "device_fp2",
# "device_sp2",
# "device_p2",
# "device_fd3",
# "device_sd3",
# "device_fs3",
# "device_ss3",
# "device_fp3",
# "device_sp3",
# "device_p3",
]
CROSS_COLUMNS = [
["device_fd", "content_fd"],
......@@ -434,21 +434,21 @@ def join_features(device_df, tractate_df, cc_df):
df["device_sp"] = df["second_positions_x"].apply(lambda x: nth_element(x, 0))
df["device_p"] = df["projects_x"].apply(lambda x: nth_element(x, 0))
df["device_fd2"] = df["first_demands_x"].apply(lambda x: nth_element(x, 1))
df["device_sd2"] = df["second_demands_x"].apply(lambda x: nth_element(x, 1))
df["device_fs2"] = df["first_solutions_x"].apply(lambda x: nth_element(x, 1))
df["device_ss2"] = df["second_solutions_x"].apply(lambda x: nth_element(x, 1))
df["device_fp2"] = df["first_positions_x"].apply(lambda x: nth_element(x, 1))
df["device_sp2"] = df["second_positions_x"].apply(lambda x: nth_element(x, 1))
df["device_p2"] = df["projects_x"].apply(lambda x: nth_element(x, 1))
# df["device_fd2"] = df["first_demands_x"].apply(lambda x: nth_element(x, 1))
# df["device_sd2"] = df["second_demands_x"].apply(lambda x: nth_element(x, 1))
# df["device_fs2"] = df["first_solutions_x"].apply(lambda x: nth_element(x, 1))
# df["device_ss2"] = df["second_solutions_x"].apply(lambda x: nth_element(x, 1))
# df["device_fp2"] = df["first_positions_x"].apply(lambda x: nth_element(x, 1))
# df["device_sp2"] = df["second_positions_x"].apply(lambda x: nth_element(x, 1))
# df["device_p2"] = df["projects_x"].apply(lambda x: nth_element(x, 1))
df["device_fd3"] = df["first_demands_x"].apply(lambda x: nth_element(x, 2))
df["device_sd3"] = df["second_demands_x"].apply(lambda x: nth_element(x, 2))
df["device_fs3"] = df["first_solutions_x"].apply(lambda x: nth_element(x, 2))
df["device_ss3"] = df["second_solutions_x"].apply(lambda x: nth_element(x, 2))
df["device_fp3"] = df["first_positions_x"].apply(lambda x: nth_element(x, 2))
df["device_sp3"] = df["second_positions_x"].apply(lambda x: nth_element(x, 2))
df["device_p3"] = df["projects_x"].apply(lambda x: nth_element(x, 2))
# df["device_fd3"] = df["first_demands_x"].apply(lambda x: nth_element(x, 2))
# df["device_sd3"] = df["second_demands_x"].apply(lambda x: nth_element(x, 2))
# df["device_fs3"] = df["first_solutions_x"].apply(lambda x: nth_element(x, 2))
# df["device_ss3"] = df["second_solutions_x"].apply(lambda x: nth_element(x, 2))
# df["device_fp3"] = df["first_positions_x"].apply(lambda x: nth_element(x, 2))
# df["device_sp3"] = df["second_positions_x"].apply(lambda x: nth_element(x, 2))
# df["device_p3"] = df["projects_x"].apply(lambda x: nth_element(x, 2))
df["content_fd"] = df["first_demands_y"].apply(lambda x: nth_element(x, 0))
df["content_sd"] = df["second_demands_y"].apply(lambda x: nth_element(x, 0))
......@@ -538,20 +538,20 @@ def device_tractate_fe(device_id, tractate_ids, device_dict, tractate_dict):
device_info["device_fp"] = nth_element(device_fp, 0)
device_info["device_sp"] = nth_element(device_sp, 0)
device_info["device_p"] = nth_element(device_p, 0)
device_info["device_fd2"] = nth_element(device_fd, 1)
device_info["device_sd2"] = nth_element(device_sd, 1)
device_info["device_fs2"] = nth_element(device_fs, 1)
device_info["device_ss2"] = nth_element(device_ss, 1)
device_info["device_fp2"] = nth_element(device_fp, 1)
device_info["device_sp2"] = nth_element(device_sp, 1)
device_info["device_p2"] = nth_element(device_p, 1)
device_info["device_fd3"] = nth_element(device_fd, 2)
device_info["device_sd3"] = nth_element(device_sd, 2)
device_info["device_fs3"] = nth_element(device_fs, 2)
device_info["device_ss3"] = nth_element(device_ss, 2)
device_info["device_fp3"] = nth_element(device_fp, 2)
device_info["device_sp3"] = nth_element(device_sp, 2)
device_info["device_p3"] = nth_element(device_p, 2)
# device_info["device_fd2"] = nth_element(device_fd, 1)
# device_info["device_sd2"] = nth_element(device_sd, 1)
# device_info["device_fs2"] = nth_element(device_fs, 1)
# device_info["device_ss2"] = nth_element(device_ss, 1)
# device_info["device_fp2"] = nth_element(device_fp, 1)
# device_info["device_sp2"] = nth_element(device_sp, 1)
# device_info["device_p2"] = nth_element(device_p, 1)
# device_info["device_fd3"] = nth_element(device_fd, 2)
# device_info["device_sd3"] = nth_element(device_sd, 2)
# device_info["device_fs3"] = nth_element(device_fs, 2)
# device_info["device_ss3"] = nth_element(device_ss, 2)
# device_info["device_fp3"] = nth_element(device_fp, 2)
# device_info["device_sp3"] = nth_element(device_sp, 2)
# device_info["device_p3"] = nth_element(device_p, 2)
tractate_lst = []
tractate_ids_res = []
for id in tractate_ids:
......
src/models/esmm/tractate_model.py
View file @ d4f9db15
......@@ -167,20 +167,20 @@ _categorical_columns = [
"click_tractate_id4",
"click_tractate_id5",
"service_city",
"device_fd2",
"device_sd2",
"device_fs2",
"device_ss2",
"device_fp2",
"device_sp2",
"device_p2",
"device_fd3",
"device_sd3",
"device_fs3",
"device_ss3",
"device_fp3",
"device_sp3",
"device_p3",
# "device_fd2",
# "device_sd2",
# "device_fs2",
# "device_ss2",
# "device_fp2",
# "device_sp2",
# "device_p2",
# "device_fd3",
# "device_sd3",
# "device_fs3",
# "device_ss3",
# "device_fp3",
# "device_sp3",
# "device_p3",
]
PREDICTION_ALL_COLUMNS = _int_columns + _float_columns + _categorical_columns
......
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