/usr/bin/python2.7 /mnt/Data/Projects/ecomobi-microservice/topica_analytic.py
INFO:common.jdbc:Connecting to database
	->dbname='fb_detail' user='ecodata' host='104.199.222.244' port='5432' password='Eco12387654'
INFO:parameter:Load 907 ids of universities
INFO:parameter:Load 63 ids of provinces
INFO:parameter:Load 7 ids of school types
INFO:parameter:Load 19 ids of majors
/home/chiennd/.local/lib/python2.7/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.
  "This module will be removed in 0.20.", DeprecationWarning)
INFO:common.jdbc:Connecting to database
	->dbname='topica' user='ecomobi' host='localhost' port='2222' password='OD4o9ammD42'
INFO:__main__:Reading data....
sys:1: DtypeWarning: Columns (130,131,132,133) have mixed types. Specify dtype option on import or set low_memory=False.
INFO:__main__:Finish reading data, shape of data: (100361, 137)
INFO:__main__:Create extractor...
['Unnamed: 0' 'cds_id' 'label' 'mobile' 'id' 'age' 'birthday_year' 'gender'
 'birthday_month' 'birthday_day' 'education' 'work' 'oid' 'address' 'email'
 'first_name' 'hometown' 'locale' 'middle_name' 'last_name' 'phone'
 'relationship_status' 'birth_day' 'fb_id' 'id.1' 'schools'
 'highest_school_degree' 'majors' 'university' 'university_type'
 'university_location' 'id.2' 'hometown_province_id' 'location_province_id'
 'hometown.1' 'location' 'mobile.1' 'id.3' 'value' 'name' 'loc' 'id.4'
 'value.1' 'name.1' 'loc.1' 'cds_id.1' 'email_status'
 'is_email_related_name' 'is_beautiful_mobile_number' 'email.1' 'mobile.2'
 'name.2' 'age_email' 'age_mobile' 'company_email' 'email_name_status'
 'event_type' 'vid' 'statuscall' 'utm_id' 'nganhdk' 'trinhdo'
 'registereddate' 'nganhhoc' 'location_id' 'email.2' 'diemtuyensinh'
 'datelevel3a' 'datelevel3b' 'datelevel3c' 'calldate' 'schoolgrad' 'tvts'
 'callamount' 'totnghiep' 'datelevel1' 'datelevel2' 'datelevel4'
 'datelevel5' 'datelevel6' 'sid' 'datelevel8' 'majorname' 'age.1' 'c5'
 'landing_id' 'school' 'statuscare' 'level' 'mobile.3' 'gender.1' 'notes'
 'datelevel7' 'handoverdate' 'truongdk' 'fullname' 'device_id' 'isc5'
 'cds_id.2' 'appointmentdate' 'sourcetype' 'keyword' 'cid' 'number_contact'
 'created_at' 'c5_date' 'url_id' 'email2' 'id.5' 'sub_id' 'status'
 'crm_status' '_id' 'utm_campaign' 'code_chanel' 'utm_term' 'utm_content'
 'utm_source' 'utm_medium' 'utm_agent' 'utm_team' 'channel' 'cds_id.3'
 'mobile_number' 'mobile_networks' '_id.1' 'landingpage_version'
 'landing_page' 'mau_qc' 'san_pham' 'id_campaign' 'property_aid'
 'id_camp_landingpage' 'id_landingpage' 'kenh_con' 'property_code'
 'olm_onboarding']
['Unnamed: 0' 'cds_id' 'label' 'mobile' 'id' 'age' 'birthday_year' 'gender'
 'birthday_month' 'birthday_day' 'education' 'work' 'oid' 'address' 'email'
 'first_name' 'hometown' 'locale' 'middle_name' 'last_name' 'phone'
 'relationship_status' 'birth_day' 'fb_id' 'id.1' 'schools'
 'highest_school_degree' 'majors' 'university' 'university_type'
 'university_location' 'id.2' 'hometown_province_id' 'location_province_id'
 'hometown.1' 'location' 'mobile.1' 'id.3' 'value' 'name' 'loc' 'id.4'
 'value.1' 'name.1' 'loc.1' 'cds_id.1' 'email_status'
 'is_email_related_name' 'is_beautiful_mobile_number' 'email.1' 'mobile.2'
 'name.2' 'age_email' 'age_mobile' 'company_email' 'email_name_status'
 'event_type' 'vid' 'statuscall' 'utm_id' 'nganhdk' 'trinhdo'
 'registereddate' 'nganhhoc' 'location_id' 'email.2' 'diemtuyensinh'
 'datelevel3a' 'datelevel3b' 'datelevel3c' 'calldate' 'schoolgrad' 'tvts'
 'callamount' 'totnghiep' 'datelevel1' 'datelevel2' 'datelevel4'
 'datelevel5' 'datelevel6' 'sid' 'datelevel8' 'majorname' 'age.1' 'c5'
 'landing_id' 'school' 'statuscare' 'level' 'mobile.3' 'gender.1' 'notes'
 'datelevel7' 'handoverdate' 'truongdk' 'fullname' 'device_id' 'isc5'
 'cds_id.2' 'appointmentdate' 'sourcetype' 'keyword' 'cid' 'number_contact'
 'created_at' 'c5_date' 'url_id' 'email2' 'id.5' 'sub_id' 'status'
 'crm_status' '_id' 'utm_campaign' 'code_chanel' 'utm_term' 'utm_content'
 'utm_source' 'utm_medium' 'utm_agent' 'utm_team' 'channel' 'cds_id.3'
 'mobile_number' 'mobile_networks' '_id.1' 'landingpage_version'
 'landing_page' 'mau_qc' 'san_pham' 'id_campaign' 'property_aid'
 'id_camp_landingpage' 'id_landingpage' 'kenh_con' 'property_code'
 'olm_onboarding']
After clean: (97279, 37)
After clean: (3082, 37)
------------------------- Time 0 ---------------------------
Train (90324, 37)
Test (10037, 37)
Number of true-predicted items: 9805
Number of false-predicted items: 232
Label: [ 0.  1.]
True by label: [9700  105]
False by label: [ 28 204]
Accuracy - 0 - 1 - total: [ 0.99712171  0.33980583  0.97688552]
------------------------- Time 1 ---------------------------
Train (90324, 37)
Test (10037, 37)
Number of true-predicted items: 9806
Number of false-predicted items: 231
Label: [ 0.  1.]
True by label: [9695  111]
False by label: [ 33 198]
Accuracy - 0 - 1 - total: [ 0.99660773  0.3592233   0.97698515]
------------------------- Time 2 ---------------------------
Train (90325, 37)
Test (10036, 37)
Number of true-predicted items: 9808
Number of false-predicted items: 228
Label: [ 0.  1.]
True by label: [9707  101]
False by label: [ 21 207]
Accuracy - 0 - 1 - total: [ 0.99784128  0.32792208  0.97728179]
------------------------- Time 3 ---------------------------
Train (90325, 37)
Test (10036, 37)
Number of true-predicted items: 9807
Number of false-predicted items: 229
Label: [ 0.  1.]
True by label: [9690  117]
False by label: [ 38 191]
Accuracy - 0 - 1 - total: [ 0.99609375  0.37987013  0.97718214]
------------------------- Time 4 ---------------------------
Train (90325, 37)
Test (10036, 37)
Number of true-predicted items: 9808
Number of false-predicted items: 228
Label: [ 0.  1.]
True by label: [9701  107]
False by label: [ 27 201]
Accuracy - 0 - 1 - total: [ 0.99722451  0.3474026   0.97728179]
------------------------- Time 5 ---------------------------
Train (90325, 37)
Test (10036, 37)
Number of true-predicted items: 9802
Number of false-predicted items: 234
Label: [ 0.  1.]
True by label: [9692  110]
False by label: [ 36 198]
Accuracy - 0 - 1 - total: [ 0.99629934  0.35714286  0.97668394]
------------------------- Time 6 ---------------------------
Train (90325, 37)
Test (10036, 37)
Number of true-predicted items: 9830
Number of false-predicted items: 206
Label: [ 0.  1.]
True by label: [9713  117]
False by label: [ 15 191]
Accuracy - 0 - 1 - total: [ 0.99845806  0.37987013  0.97947389]
------------------------- Time 7 ---------------------------
Train (90325, 37)
Test (10036, 37)
Number of true-predicted items: 9807
Number of false-predicted items: 229
Label: [ 0.  1.]
True by label: [9699  108]
False by label: [ 29 200]
Accuracy - 0 - 1 - total: [ 0.99701891  0.35064935  0.97718214]
------------------------- Time 8 ---------------------------
Train (90325, 37)
Test (10036, 37)
Number of true-predicted items: 9788
Number of false-predicted items: 248
Label: [ 0.  1.]
True by label: [9701   87]
False by label: [ 27 221]
Accuracy - 0 - 1 - total: [ 0.99722451  0.28246753  0.97528896]
------------------------- Time 9 ---------------------------
Train (90326, 37)
Test (10035, 37)
Number of true-predicted items: 9813
Number of false-predicted items: 222
Label: [ 0.  1.]
True by label: [9702  111]
False by label: [ 25 197]
Accuracy - 0 - 1 - total: [ 0.99742983  0.36038961  0.97787743]
[array([ 0.99712171,  0.33980583,  0.97688552]), array([ 0.99660773,  0.3592233 ,  0.97698515]), array([ 0.99784128,  0.32792208,  0.97728179]), array([ 0.99609375,  0.37987013,  0.97718214]), array([ 0.99722451,  0.3474026 ,  0.97728179]), array([ 0.99629934,  0.35714286,  0.97668394]), array([ 0.99845806,  0.37987013,  0.97947389]), array([ 0.99701891,  0.35064935,  0.97718214]), array([ 0.99722451,  0.28246753,  0.97528896]), array([ 0.99742983,  0.36038961,  0.97787743])]
Final [ 0.99713196  0.34847434  0.97721228]