rate_of_changeLibrary "rate_of_change"
// @description: Applies ROC algorithm to any pair of values.
// This library function is used to scale change of value (price, volume) to a percentage value, just as the ROC indicator would do. It is good practice to scale arbitrary ranges to set boundaries when you try to train statistical model.
rateOfChange(value, base, hardlimit)
This function is a helper to scale a value change to its percentage value.
Parameters:
value (float)
base (float)
hardlimit (int)
Returns: per: A float comprised between 0 and 100
Scaling
Feature ScalingLibrary "Feature_Scaling"
FS: This library helps you scale your data to certain ranges or standarize, normalize, unit scale or min-max scale your data in your prefered way. Mostly used for normalization purposes.
minmaxscale(source, min, max, length)
minmaxscale: Min-max normalization scales your data to set minimum and maximum range
Parameters:
source
min
max
length
Returns: res: Data scaled to the set minimum and maximum range
meanscale(source, length)
meanscale: Mean normalization of your data
Parameters:
source
length
Returns: res: Mean normalization result of the source
standarize(source, length, biased)
standarize: Standarization of your data
Parameters:
source
length
biased
Returns: res: Standarized data
unitlength(source, length)
unitlength: Scales your data into overall unit length
Parameters:
source
length
Returns: res: Your data scaled to the unit length
