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System and method of pre-processing discrete datasets for use in machine learning

机译:用于预处理离散数据集的系统和方法,用于机器学习

摘要

There is provided a system and method of pre-processing discrete datasets for use in machine learning. The method includes: determining a median and a standard deviation of an input discrete dataset; determining a probability mass function including a probability of finding a particular data point in the input discrete dataset within a particular bin of a histogram representative of the input discrete dataset; transforming the probability mass function into a continuously differentiable probability density function using the standard deviation, the probability density function determined using a parametric control function, the parametric control function including a lognormal derivative of the probability density function, the parameters within the control function are estimated using optimization that minimizes a mean-squared error of an objective function; and outputting the probability density function for use an input to a machine learning model.
机译:提供了一种用于预处理离散数据集的系统和方法,用于用于机器学习。该方法包括:确定输入离散数据集的中值和标准偏差;确定概率质量函数,包括在输入离散数据集的直方图的特定箱内找到输入的离散数据集中的特定数据点的概率;使用标准偏差将概率质量函数变换为连续可分辨率的概率密度函数,使用参数控制功能确定的概率密度函数,参数控制功能包括概率密度函数的逻辑衍生物,估计控制功能内的参数使用优化使目标函数的平均平均误差最小化;并输出对机器学习模型的输入使用输入的概率密度函数。

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