post https://api-lib.bambu.life/api/autoMl/v2/numericFeaturesInfo
This endpoint aims to list characteristics of selected numeric features, such as mean, standard deviation, skewness, kurtosis, as well as x and y values for histogram.
Request Body
Name | Datatype | Description | Mandatory | Sample Value | List of possible values | Notes |
---|---|---|---|---|---|---|
clientId | String | It is meant for identification purpose as information are stored under unique id value | Yes | |||
numericFeatures | List of strings | Numerical features are required in order to compute some statistical information, such as average, density, and many more | Yes | ["age", "personalIncome"] | Depends on the values derived from /data_retrieval endpoint based on the client_id value. The values must fall under numerical features | The value in the array must match with the set key-value pair found in /data_retrieval endpoint based on the client_id value. The values must fall under numerical features |
Response Body
Name | Datatype | Description | No. of decimals | Notes |
---|---|---|---|---|
numericFeatureInfo value placeholder | Array of dictionary | An array containing the information for numeric features users are interested in. | Payload is the same for each item in numeric_features. | |
name | String | Name of numeric feature | ||
info | Dictionary | A dictionary containing average, kurtosis, skewness, standard deviation, density and histogram data | ||
average | Number | Average value of the numeric feature | 5 | |
density | Array | An array of the x_cord and respective value | 5 | |
densityValue | Number | 5 | ||
xValue | Number | X coordinate value | 5 | |
hist | Array | An array of the count, densityValue, xHighValue, xLowValue and xMidvalue needed to make a histogram. | ||
count | Integer | 0 | ||
densityValue | Number | 5 | ||
xHighValue | Number | X coordinate high value | 5 | |
xLowValue | Number | X coordinate low value | 5 | |
xMidValue | Number | X coordinate mid value | 5 | |
kurtosis | number | Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. That is, data sets with high kurtosis tend to have heavy tails, or outliers. Data sets with low kurtosis tend to have light tails, or lack of outliers. A uniform distribution would be the extreme case. | 5 | |
skewness | number | Skewness is a measure of symmetry, or more precisely, the lack of symmetry. A distribution, or data set, is symmetric if it looks the same to the left and right of the center point. | 5 | |
standardDeviation | number | The standard deviation is a measure of how spread out numbers are. | 5 |