In this research, we try to overcome the outlier problem in the heart disease dataset using one of the feature scaling methods, namely the robust scaler. Experimental results with the K-Nearest Neighbors algorithm classification model using the robust scaler scaling method obtained b...
Sparklyr 1.4 is now available! This release comes with delightful new features such as weighted sampling and tidyr verbs support for Spark dataframes, robust scaler for standardizing data based on median and interquartile range, spark_connect interface..
In this research, we try to overcome the outlier problem in the heart disease dataset using one of the feature scaling methods, namely the robust scaler. Experimental results with the K-Nearest Neighbors algorithm classification model using the robust scaler scaling method obtained better scores ...
Under this background, a robust non-negative least mean square (R-NNLMS) algorithm based on a step-size scaler is proposed. The proposed algorithm uses a step-size scaler to avoid the influence of impulsive noise. For various outliers, the step-size scaler can adjust the step size of the...