Description
For lowerCutpoint<upperCutpoint return normalized=(value-lower)/(upper-lower), below=(value<lower), and above=(value>upper).
Normalization depends on the supplied center, scale, norm, range, reference distribution, or denominator. A zero spread and a missing denominator need an explicit policy, and clipping differs from fitting a scaler. Evaluating one scalar or derivative term does not estimate every parameter or establish a distributional improvement.
For lowerCutpoint<upperCutpoint return normalized=(value-lower)/(upper-lower), below=(value<lower), and above=(value>upper).
When to use this tool
Use Percentile Scaler Explicit Cutpoint Gap when you already have the required normalization parameters and need this local scalar, range, policy, or derivative term.
How to use the tool and how it works
- Enter value, lowerCutpoint, upperCutpoint. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read normalized, below, above. Inspect below, above before interpreting the associated values.
For lowerCutpoint<upperCutpoint return normalized=(value-lower)/(upper-lower), below=(value<lower), and above=(value>upper).1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| value | Supplied scalar or returned value under the stated operation. | Required. Finite number. |
| lowerCutpoint | Lower Cutpoint | Required. Finite number. |
| upperCutpoint | Upper Cutpoint | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| normalized | Scalar transformed under the stated formula and zero policy. | Required. Finite number. |
| below | Below | Required. Boolean. |
| above | Above | Required. Boolean. |
{
"input": {
"value": 12,
"lowerCutpoint": 2,
"upperCutpoint": 10
},
"output": {
"normalized": 1.25,
"below": false,
"above": true
}
}Limitations and assumptions
- Cutpoints are supplied rather than calculated percentiles. Out-of-range values are retained instead of clipped, exact boundary values set neither flag, and no distribution or outlier policy is fitted.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Fit or verify the intended scaler parameters and statistical model separately. Check units, zero policies, missingness, clipping, inverse conventions, and whether supplied norms or denominators belong to the same data.
References
Similar or alternative tools
- Winsorized Value Clipping Displacement
Return value as the clipped result and displacement=clipped-original.
- Minmax Inverse Parameter Consistency
For minimum<maximum return reconstructed=minimum+normalized*(maximum-minimum) and residual=value-reconstructed.