MaxAbs

class geoanalytics.normalization.MaxAbs.MaxAbs(dataframe)

Bases: object

About this algorithm

Description:

MaxAbs is a normalization technique that scales each feature by its maximum absolute value. It is particularly useful when features contain both positive and negative values, ensuring all values lie within the range [-1, 1]. This class also tracks runtime and memory usage.

Parameters:

• dataframe (pd.DataFrame): Input DataFrame containing ‘x’, ‘y’, and feature columns.

Attributes:

• df (pd.DataFrame) – Original DataFrame with standardized column names.

• normalizedDF (pd.DataFrame) – Output DataFrame after MaxAbs scaling.

• startTime, endTime (float) – Time tracking variables.

• memoryUSS, memoryRSS (float) – Memory usage in kilobytes (USS and RSS).

Execution methods

Calling from a Python program

import pandas as pd

from geoanalytics.normalization import MaxAbs

df = pd.read_csv("input.csv")

scaler = MaxAbs(df)

normalized_df = scaler.run()

scaler.getRuntime()

scaler.getMemoryUSS()

scaler.getMemoryRSS()

scaler.save("MaxAbs.csv")

Credits

This implementation was created by Raashika and revised by M. Charan Teja under the guidance of Professor Rage Uday Kiran.

getMemoryRSS()

Prints the memory usage (RSS) of the process in kilobytes.

getMemoryUSS()

Prints the memory usage (USS) of the process in kilobytes.

getRuntime()

Prints the total runtime of the clustering algorithm.

run()

Executes the MaxAbs scaling normalization on the dataset.

Returns:

DataFrame containing ‘x’, ‘y’, and MaxAbs-normalized feature values.

Return type:

pd.DataFrame

save(outputFile='MaxAbs.csv')

Saves the Normalized DataFrame to a CSV file.