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https://issues.apache.org/jira/browse/SPARK-8284?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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李力 updated SPARK-8284:
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Description:
Extreme Learning Machine can get better generalization performance at a much
faster learning speed for regression and classification problem，but the
enlarging volume of datasets makes regression by ELM on very large scale
datasets a challenging task.
Through analyzing the mechanism of ELM algorithm , an efficient parallel ELM
for regression is designed and implemented based on Spark.
The experimental results demonstrate that the propose parallel ELM for
regression can efficiently handle very large dataset with a good performance.
was:
Extreme Learning Machine can get better generalization performance at a mauch
faster learning speed for regression and classification problem，but the
enlarging volume of datasets makes regression by ELM on very large scala
datasets a challenging task.
Through analyzing the mechanism of ELM algorithm , an efficient parallel ELM
for regression is designed and implemented based on Spark.
The experimental results demonstrate that the propose parallel ELM for
regresssion can efficiently handle very large dataset with a good performance.
> Regualarized Extreme Learning Machine for MLLib
> -----------------------------------------------
>
> Key: SPARK-8284
> URL: https://issues.apache.org/jira/browse/SPARK-8284
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 1.3.1
> Reporter: 李力
>
> Extreme Learning Machine can get better generalization performance at a much
> faster learning speed for regression and classification problem，but the
> enlarging volume of datasets makes regression by ELM on very large scale
> datasets a challenging task.
> Through analyzing the mechanism of ELM algorithm , an efficient parallel ELM
> for regression is designed and implemented based on Spark.
> The experimental results demonstrate that the propose parallel ELM for
> regression can efficiently handle very large dataset with a good performance.
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