Example Anchors Tabular Explaination for Income Prediction¶
This example uses a US income dataset to show the example of explanation on tabular data. You can also try out the Jupyter notebook for a visual walkthrough.
Create the InferenceService with alibi explainer¶
We can create a InferenceService with a trained sklearn predictor for this dataset and an associated model explainer. The black box explainer algorithm we will use is the Tabular version of Anchors from the Alibi open source library. More details on this algorithm and configuration settings that can be set can be found in the Seldon Alibi documentation.
The InferenceService is shown below:
apiVersion: "serving.kserve.io/v1beta1"
kind: "InferenceService"
metadata:
name: "income"
spec:
predictor:
minReplicas: 1
sklearn:
storageUri: "gs://kfserving-examples/models/sklearn/1.3/income/model"
resources:
requests:
cpu: 0.1
memory: 1Gi
limits:
cpu: 1
memory: 1Gi
explainer:
minReplicas: 1
alibi:
type: AnchorTabular
storageUri: "gs://kfserving-examples/models/sklearn/1.3/income/explainer"
resources:
requests:
cpu: 0.1
memory: 1Gi
limits:
cpu: 1
memory: 4Gi
Create the InferenceService with above yaml:
kubectl create -f income.yaml
The first step is to determine the ingress IP and ports and set INGRESS_HOST and INGRESS_PORT
MODEL_NAME=income
SERVICE_HOSTNAME=$(kubectl get inferenceservice income -o jsonpath='{.status.url}' | cut -d "/" -f 3)
Run the inference¶
Test the predictor:
curl -H "Host: $SERVICE_HOSTNAME" -H "Content-Type: application/json" http://${INGRESS_HOST}:${INGRESS_PORT}/v1/models/$MODEL_NAME:predict -d '{"instances":[[39, 7, 1, 1, 1, 1, 4, 1, 2174, 0, 40, 9]]}'
You should receive the response showing the prediction is for low salary:
Expected Output
{"predictions": [0]}
Run the explanation¶
Now lets get an explanation for this:
curl -H "Host: $SERVICE_HOSTNAME" -H "Content-Type: application/json" http://${INGRESS_HOST}:${INGRESS_PORT}/v1/models/$MODEL_NAME:explain -d '{"instances":[[39, 7, 1, 1, 1, 1, 4, 1, 2174, 0, 40, 9]]}'
The returned explanation will be like:
Expected Output
{
"names": [
"Marital Status = Never-Married",
"Workclass = State-gov"
],
"precision": 0.9724770642201835,
"coverage": 0.0147,
"raw": {
"feature": [
3,
1
],
"mean": [
0.9129746835443038,
0.9724770642201835
],
"precision": [
0.9129746835443038,
0.9724770642201835
],
"coverage": [
0.3327,
0.0147
],
"examples": [
{
"covered": [
[
30,
"Self-emp-not-inc",
"Bachelors",
"Never-Married",
"Sales",
"Unmarried",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
69,
"Private",
"Dropout",
"Never-Married",
"Blue-Collar",
"Husband",
"White",
"Male",
9386,
"Capital Loss <= 0.00",
60,
"United-States"
],
[
44,
"Local-gov",
"Bachelors",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
52,
"United-States"
],
[
59,
"Private",
"High School grad",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
50,
"United-States"
],
[
55,
"Private",
"Bachelors",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
15024,
"Capital Loss <= 0.00",
55,
"United-States"
],
[
32,
"?",
"Bachelors",
"Never-Married",
"?",
"Unmarried",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
32,
"United-States"
],
[
47,
"Private",
"Dropout",
"Never-Married",
"Blue-Collar",
"Unmarried",
"Black",
"Female",
6849,
"Capital Loss <= 0.00",
40,
"United-States"
],
[
35,
"Private",
"Associates",
"Never-Married",
"Service",
"Not-in-family",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
65,
"United-States"
],
[
32,
"Private",
"High School grad",
"Never-Married",
"Blue-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
48,
"Private",
"Masters",
"Never-Married",
"White-Collar",
"Husband",
"Black",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
45,
"United-States"
]
],
"covered_true": [
[
32,
"Private",
"High School grad",
"Never-Married",
"Blue-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
44,
"Local-gov",
"Bachelors",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
52,
"United-States"
],
[
36,
"Private",
"High School grad",
"Never-Married",
"Blue-Collar",
"Unmarried",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
30,
"United-States"
],
[
56,
"Private",
"High School grad",
"Never-Married",
"Blue-Collar",
"Unmarried",
"Black",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
49,
"Local-gov",
"High School grad",
"Never-Married",
"Service",
"Unmarried",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
30,
"United-States"
],
[
20,
"?",
"High School grad",
"Never-Married",
"?",
"Own-child",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
10,
"United-States"
],
[
22,
"?",
"High School grad",
"Never-Married",
"?",
"Own-child",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
"Hours per week > 45.00",
"United-States"
],
[
29,
"Private",
"High School grad",
"Never-Married",
"Service",
"Own-child",
"Asian-Pac-Islander",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
25,
"SE-Asia"
],
[
45,
"Local-gov",
"Masters",
"Never-Married",
"Professional",
"Unmarried",
"White",
"Female",
1506,
"Capital Loss <= 0.00",
45,
"United-States"
],
[
27,
"Private",
"High School grad",
"Never-Married",
"Blue-Collar",
"Not-in-family",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
50,
"United-States"
]
],
"covered_false": [
[
29,
"Private",
"Bachelors",
"Never-Married",
"Service",
"Husband",
"White",
"Male",
7298,
"Capital Loss <= 0.00",
42,
"United-States"
],
[
56,
"Private",
"Associates",
"Never-Married",
"Sales",
"Husband",
"White",
"Male",
15024,
"Capital Loss <= 0.00",
40,
"United-States"
],
[
47,
"Private",
"Masters",
"Never-Married",
"Sales",
"Not-in-family",
"White",
"Male",
27828,
"Capital Loss <= 0.00",
60,
"United-States"
],
[
40,
"Private",
"Associates",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
7688,
"Capital Loss <= 0.00",
44,
"United-States"
],
[
55,
"Self-emp-not-inc",
"High School grad",
"Never-Married",
"White-Collar",
"Not-in-family",
"White",
"Male",
34095,
"Capital Loss <= 0.00",
60,
"United-States"
],
[
53,
"Private",
"Masters",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
48,
"United-States"
],
[
47,
"Federal-gov",
"Doctorate",
"Never-Married",
"Professional",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
53,
"Private",
"High School grad",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
1977,
40,
"United-States"
],
[
46,
"Private",
"Bachelors",
"Never-Married",
"Sales",
"Not-in-family",
"White",
"Male",
8614,
"Capital Loss <= 0.00",
40,
"United-States"
],
[
44,
"Local-gov",
"Prof-School",
"Never-Married",
"Professional",
"Not-in-family",
"White",
"Male",
10520,
"Capital Loss <= 0.00",
40,
"United-States"
]
],
"uncovered_true": [],
"uncovered_false": []
},
{
"covered": [
[
41,
"State-gov",
"High School grad",
"Never-Married",
"White-Collar",
"Not-in-family",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
64,
"State-gov",
"High School grad",
"Never-Married",
"Blue-Collar",
"Not-in-family",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
33,
"State-gov",
"High School grad",
"Never-Married",
"Service",
"Unmarried",
"Black",
"Female",
1831,
"Capital Loss <= 0.00",
40,
"United-States"
],
[
35,
"State-gov",
"High School grad",
"Never-Married",
"Blue-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
60,
"United-States"
],
[
25,
"State-gov",
"Dropout",
"Never-Married",
"Blue-Collar",
"Own-child",
"Black",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
40,
"State-gov",
"Associates",
"Never-Married",
"Blue-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
19,
"State-gov",
"High School grad",
"Never-Married",
"Blue-Collar",
"Other-relative",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
20,
"United-States"
],
[
44,
"State-gov",
"Dropout",
"Never-Married",
"Blue-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
88,
"United-States"
],
[
80,
"State-gov",
"Associates",
"Never-Married",
"Blue-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
24,
"United-States"
],
[
21,
"State-gov",
"High School grad",
"Never-Married",
"Professional",
"Own-child",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
20,
"United-States"
]
],
"covered_true": [
[
22,
"State-gov",
"High School grad",
"Never-Married",
"Service",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
25,
"United-States"
],
[
49,
"State-gov",
"High School grad",
"Never-Married",
"Service",
"Not-in-family",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
22,
"State-gov",
"Bachelors",
"Never-Married",
"?",
"Not-in-family",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
25,
"United-States"
],
[
31,
"State-gov",
"Bachelors",
"Never-Married",
"Professional",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
50,
"United-States"
],
[
18,
"State-gov",
"Dropout",
"Never-Married",
"Blue-Collar",
"Not-in-family",
"Black",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
56,
"State-gov",
"High School grad",
"Never-Married",
"Blue-Collar",
"Unmarried",
"Black",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
26,
"State-gov",
"Dropout",
"Never-Married",
"Service",
"Unmarried",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
38,
"State-gov",
"Bachelors",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
52,
"State-gov",
"High School grad",
"Never-Married",
"Blue-Collar",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
70,
"United-States"
],
[
25,
"State-gov",
"Associates",
"Never-Married",
"Professional",
"Wife",
"White",
"Female",
"Capital Gain <= 0.00",
1887,
40,
"United-States"
]
],
"covered_false": [
[
46,
"State-gov",
"Prof-School",
"Never-Married",
"Professional",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
45,
"United-States"
],
[
42,
"State-gov",
"Bachelors",
"Never-Married",
"White-Collar",
"Husband",
"White",
"Male",
15024,
"Capital Loss <= 0.00",
50,
"United-States"
],
[
46,
"State-gov",
"Prof-School",
"Never-Married",
"Professional",
"Husband",
"White",
"Male",
15024,
"Capital Loss <= 0.00",
40,
"United-States"
],
[
54,
"State-gov",
"Doctorate",
"Never-Married",
"White-Collar",
"Not-in-family",
"White",
"Female",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
40,
"United-States"
],
[
42,
"State-gov",
"Masters",
"Never-Married",
"White-Collar",
"Not-in-family",
"White",
"Female",
14084,
"Capital Loss <= 0.00",
60,
"United-States"
],
[
37,
"State-gov",
"Masters",
"Never-Married",
"Professional",
"Husband",
"White",
"Male",
"Capital Gain <= 0.00",
"Capital Loss <= 0.00",
45,
"United-States"
]
],
"uncovered_true": [],
"uncovered_false": []
}
],
"all_precision": 0,
"num_preds": 1000101,
"names": [
"Marital Status = Never-Married",
"Workclass = State-gov"
],
"instance": [
[
39
],
[
7
],
[
"28.00 < Age <= 37.00"
],
[
"28.00 < Age <= 37.00"
],
[
"28.00 < Age <= 37.00"
],
[
"28.00 < Age <= 37.00"
],
[
4
],
[
"28.00 < Age <= 37.00"
],
[
2174
],
[
"Age <= 28.00"
],
[
40
],
[
9
]
],
"prediction": 0
}
}