Feature Scaling

Library "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

Informacje o Wersji

v2

Updated: Fixed Descriptions
minmaxscale(source, min, max, length)
minmaxscale Min-max normalization scales your data to set minimum and maximum range
Parameters:
source: Source data you want to use
min: Minimum value you want
max: Maximum value you want
length: Length of the data you want taken into account
Returns: res Data scaled to the set minimum and maximum range

meanscale(source, length)
meanscale Mean normalization of your data
Parameters:
source: Source data you want to use
length: Length of the data you want taken into account
Returns: res Mean normalization result of the source

standarize(source, length, biased)
standarize Standarization of your data
Parameters:
source: Source data you want to use
length: Length of the data you want taken into account
biased: Whether to do biased calculation while taking standard deviation, default is true
Returns: res Standarized data

unitlength(source, length)
unitlength Scales your data into overall unit length
Parameters:
source: Source data you want to use
length: Length of the data you want taken into account
Returns: res Your data scaled to the unit length

Biblioteka Pine

W zgodzie z duchem TradingView autor opublikował ten kod Pine jako bibliotekę open-source, aby inni programiści Pine z naszej społeczności mogli go ponownie wykorzystać. Ukłony dla autora. Można korzystać z tej biblioteki prywatnie lub w innych publikacjach open-source, jednak ponowne wykorzystanie tego kodu w publikacjach podlega Zasadom serwisu.

serkany88

One does not simply win every trade.

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Biblioteka Pine

serkany88

One does not simply win every trade.

Również na: