Balanced Predictive Maintenance Dataset

Addressing Class Imbalance in Predictive Maintenance

@kaggle.chetansmahale_balanced_predictive_maintenance_dataset

Table List

9 tables(6.14 MB)

X Smote

Y Smote

X Train

Y Test

X Test

Cleaned Data

Y Train

X Ctgan

Y Ctgan

X Smote

@kaggle.chetansmahale_balanced_predictive_maintenance_dataset.x_smote

1.97 MB
47229 rows
6 columns

type Type	air_temperature_k Air Temperature [K]	process_temperature_k Process Temperature [K]	rotational_speed_rpm Rotational Speed [rpm]	torque_nm Torque [Nm]	tool_wear_min Tool Wear [min]
2	-1.4023537460317193	-1.216963430139608	0.7765934898339529	-1.192454952340947	0.3935368529396611
2	-0.3524370398513052	-0.5429545740840913	-1.142244874145794	0.6333080199205777	-1.2089526276721567
2	0.2475153636803477	1.3442702228713626	-1.5382841876416138	2.087899398920144	0.5977757083117555
1	-0.8523973761276875	-1.149562544534041	-0.5286628391522703	0.382516402851687	1.0690961437858195
1	1.947380507020036	1.950878193321312	-0.071265322157098	0.252104761975864	1.351888405070258
1	1.0974479353501918	1.0746666804491714	-0.6848473571506217	1.4157778651755175	-0.941871047570187
1	0.9474598344672714	0.602860481210279	0.4307563428376032	-0.5504284126445864	-0.9732924099351248
1	-1.3023616787764485	-0.9473598877173782	-0.4449925616531534	0.1317247857827961	1.3833097674351955
1	0.9474598344672714	0.2658560531825208	-0.115889470156627	-0.5905550713756088	0.7391718389539748
1	0.2975113973079973	-0.0037474892396704	-0.1884037106558616	-0.4099851070860077	-0.2034690319941533


CREATE TABLE x_smote (
  "type" BIGINT,
  "air_temperature_k" DOUBLE,
  "process_temperature_k" DOUBLE,
  "rotational_speed_rpm" DOUBLE,
  "torque_nm" DOUBLE,
  "tool_wear_min" DOUBLE
);