Analyze and determine based on the different Centroid Table and performance Vectors below (Gender and attrition) why is this company is losing customers (attrition rate) by using the primary attribute of gender and attribution rate to identify patterns/reasons that people are leaving ( analyze the data results and identify anomalies or reasons tobelieve people are leaving the company (lack of benefits, high APR, age group)

Centroid Tab

Attributes	Cluster 0	Clsuter 1	Cluster 2	Cluster 3	Cluster 4
Attrition Flag IF Formula = 0	0.427233	0.051435	-2.30146	0.434464	-0.05849
Attrition Flag IF Formula = 1	-0.42723	-0.05144	2.301456	-0.43446	0.058494
Gender = M	0.981201	0.292862	-0.12247	-0.61952	0.379255
Education_Level = High School	0.028531	-0.08261	-0.02406	-0.00315	0.089852
Education_Level = Graduate	-0.00931	0.05378	-0.02427	0.007693	-0.02297
Education_Level = College	-0.02738	0.010768	-0.01547	0.018719	0.085598
Education_Level = Post-Graduate	6.17E-04	0.047179	0.020685	-0.01145	-0.02878
Education_Level = Doctorate	-0.01828	-0.01253	0.075796	-0.01046	0.003131
Marital_Status = Married	0.056039	-0.18527	-0.04067	0.004453	-0.26062
Marital_Status = Single	-0.05841	0.130921	0.032173	0.005523	0.274083
Income_Category = $60K - $80K	0.644873	0.090775	-0.07308	-0.39976	0.332027
Income_Category = Less than $40K	-0.73642	-0.26211	0.082201	0.473212	-0.3041
Income_Category = $80K - $120K	0.658686	0.156513	-0.03619	-0.42204	0.106038
Income_Category = $40K - $60K	-0.33488	-6.20E-04	-0.01927	0.218947	-0.13236
Card_Category = Blue	0.26689	-3.74649	0.258771	0.266059	-3.74649
Card_Category = Gold	-0.10594	-0.10594	-0.10594	-0.10594	9.438283
Card_Category = Silver	-0.2375	4.080701	-0.2375	-0.2375	-0.2375
CLIENTNUM	0.03115	0.042247	-0.1108	0.009742	-0.00233
Customer_Age	-0.02126	-0.06015	0.04536	0.008815	-0.11171
Dependent_count	0.067306	0.063707	0.040152	-0.06745	0.246741
Months_on_book	-0.01883	-0.04943	0.03802	0.00681	-0.04576
Total_Relationship_Count	0.13248	-0.28388	-0.34009	0.065894	-0.52912
Months_Inactive_12_mon	-0.07595	-0.07153	0.355329	-0.05257	-0.03471
Contacts_Count_12_mon	-0.03766	-0.01244	0.466738	-0.11705	-0.0551
Credit_Limit	0.508504	1.869154	-0.2127	-0.51704	2.206791
Total_Revolving_Bal	0.095958	0.059956	-0.61521	0.115801	0.267644
Avg_Open_To_Buy	0.499737	1.863232	-0.15736	-0.5273	2.182111
Total_Amt_Chng_Q4_Q1	0.08459	0.015845	-0.32447	0.043592	0.053329
Total_Trans_Amt	-0.00696	0.659254	-0.45752	0.047738	0.959032
Total_Trans_Ct	-0.0199	0.427359	-0.90068	0.224884	0.675029
Total_Ct_Chng_Q4_Q1	0.123564	-0.02306	-0.70257	0.141265	-0.01444
Avg_Utilization_Ratio	-0.34747	-0.79338	-0.37358	0.440987	-0.78704

PerformanceVector - Attrition

PerformanceVector: Avg. within centroid distance: -20.495

Avg. within centroid distance_cluster_0: -22.160

Avg. within centroid distance_cluster_1: -29.642

Avg. within centroid distance_cluster_2: -23.017

Avg. within centroid distance_cluster_3: -17.500

Avg. within centroid distance_cluster_4: -28.302

Avg. within centroid distance_cluster_5: -19.414

Avg. within centroid distance_cluster_6: -19.118

Avg. within centroid distance_cluster_7: -22.268

Avg. within centroid distance_cluster_8: -17.330

Avg. within centroid distance_cluster_9: -24.104 Davies Bouldin: -2.137

Cluster Model

Cluster 0: 3027 items

Cluster 1: 550 items

Cluster 2: 1483 items

Cluster 3: 4829 items

Cluster 4: 111 items Total number of items: 10000