iRule

PatternsResource.iRule(request, sub_analysis_id, **kwargs)

Prior mandatory steps 1) Upload dataset 2) Create analysis 3) Create sub analysis 4) DataSharp

This function extracts all the hidden insight patterns on the binnedData out of dNoise. Along with patterns, this function also specifies the statistics of the patterns like Support, Lift, Confidence. Apart from this, it also gives the harmonic mean of the rule by considering all the other statistical parameters of the rule. Actionability is 0 if the pattern does not have any actionable attributes in it, whereas it is 1 if all attributes are actionable and less than 1 if some of them are actionable.

Arguments

sub_analysis_id Give sub analysis id

Possible errors

Error message
Invalid sub analysis id
Please wait for a while. Mining process is in progress
Please execute iRule first
Please execute define attributes first

POST Request Example

curl -u username:password -X POST {url_prefix}/irule/{sub_analysis_id}/?page_range=1,20

Response Example

{
    "error": false,
    "error_msg": "",
    "result": [
        {
            "actionability": "0.00",
            "confidence": "89.08",
            "display_id": "177",
            "explicability": 0.52,
            "hmean": "0.83",
            "id": 37957,
            "lift": 1.00678,
            "recommended": "No",
            "record_count": 106,
            "rule_string": "if day is less than or equal to 3 and default is no and housing is yes and pdays is less than or equal to -1 and poutcome is unknown, then y is no",
            "support": "2.34",
            "target_bin": "no"
        },
        ...
    ]
}