Benchmark test method and device of supervised learning algorithm in distributed environment

A distributed environment and benchmarking technology, applied in the field of machine learning, which can solve the problems of resource coordination, communication and consumption factors, difficulty of supervised learning algorithms, and proposal of solutions.

Inactive Publication Date: 2017-09-26
ALIBABA GRP HLDG LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] Due to the complexity of device deployment in supervised learning in a distributed environment, there are many factors in resource coordination, communication and consumption, which makes the benchmark for supervised learning algorithms in a distributed environment, t...

Method used

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  • Benchmark test method and device of supervised learning algorithm in distributed environment
  • Benchmark test method and device of supervised learning algorithm in distributed environment
  • Benchmark test method and device of supervised learning algorithm in distributed environment

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Experimental program
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Embodiment 1

[0095] refer to figure 1 , which shows a flow chart of the steps of a benchmark method embodiment of a supervised learning algorithm in a distributed environment of the present application, which may specifically include the following steps:

[0096] Step 101. Obtain the first benchmark test result determined according to the output data in the benchmark test;

[0097] Based on the output data obtained during the benchmarking process, a first benchmarking result may be determined, where the first benchmarking result is an analysis result obtained by analyzing the output data.

[0098] In a specific application, the first benchmark test result may include at least one of the following performance indicators: a true positive rate (True Positives, TP), a false positive rate (True Negative, TN), a false alarm rate ( False Positives, FP), false negative rate (False Negative, FN), precision Precision, recall rate Recall, accuracy rate Accuracy.

[0099] Step 102. Obtain the distri...

Embodiment 2

[0111] refer to figure 2 , which shows a flow chart of the steps of an embodiment of a benchmark test method for a supervised learning algorithm in a distributed environment of the present application, which may specifically include the following steps:

[0112] Step 201, determine the supervised learning algorithm to be tested;

[0113] Specifically, in this step, a supervised learning algorithm to be tested needs to be determined, and then a benchmark test is performed on the supervised learning algorithm to be tested, so as to evaluate the performance of the supervised learning algorithm to be tested.

[0114] Due to the wide application of machine learning technology, different fields will produce various learning algorithms for different application scenarios, and evaluating the performance of different learning algorithms has become an important content.

[0115] The method provided in Embodiment 2 of the present application mainly performs a benchmark test on a superv...

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Abstract

The embodiment of the invention provides a benchmark test method and device of a supervised learning algorithm in a distributed environment. The method comprises the steps that a first benchmark test result which is determined according to output data in a benchmark test is obtained; a distributed performance index in the benchmark test is obtained, and the distributed performance index is determined as a second benchmark test result; the first benchmark test result and the second benchmark test result are merged to obtain a benchmark test total result. According to a perfect scheme used for solving a benchmark test problem of the supervised learning algorithm in the distributed environment, the benchmark test method and device can assist technical staff to conduct accurate and quick assessment on the performance of the supervised learning algorithm.

Description

technical field [0001] The present application relates to the technical field of machine learning, in particular to a benchmark test method for a supervised learning algorithm in a distributed environment and a benchmark test device for a supervised learning algorithm in a distributed environment. Background technique [0002] Machine learning is a multi-field interdisciplinary subject that has emerged in the past 20 years, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. Machine learning algorithm is a kind of algorithm that automatically analyzes and obtains laws from data, and uses the laws to predict unknown data. [0003] At present, machine learning has a very wide range of applications, such as: data mining, computer vision, natural language processing, biometric recognition, search engines, medical diagnosis, detection of credit card fraud, securities market analysis, DNA sequence sequ...

Claims

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Application Information

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IPC IPC(8): G06F11/36
CPCG06F11/3688G06N20/00G06F11/3006G06F11/3428G06F11/30
Inventor 孙忠英
Owner ALIBABA GRP HLDG LTD
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