Step 5: Optimise Meta Parameters

Introduction

How It Works

Prerequisites

Administrator Account and Organisation Creation Application Creation Data Set Requirements

Step 1: Data Cleanup Step 2: Data Transformation Step 3: Upload to S3 Bucket Step 4: Sharing S3 Bucket Access to Xineoh’s API

Applications, Datasets and Schemas

Applications

Application Types

Datasets and Schemas

Minimum Requirements for Datasets and Schemas Customising Datasets and Schemas

Steps in Building a Recommender with the API

Step 1: Batch Upload Step 2: Build Data and Structures for Training and Testing Step 3: Train Model Step 4: Test Model Step 5: Optimise Meta Parameters Step 6: User-Clustering - Run Clustering, View Trade-Off, Choose Cluster Count Step 7: Item-Clustering - Run Clustering, View Trade-Off, Choose Cluster Count Step 8: Get Recommendations

Sample Implementation - Movielens 25M Dataset

S3 Bucket Creation Login as Organisation First Application Download MovieLens Preprocessed Data Upload Data to S3 Bucket Building the Recommender

Uploading S3 Bucket data to Xineoh Platform Build Data Train Test Optimization User Clustering and Trade-Off Item Clustering and Trade-Off

First Recommendations

Open Navigation

This API call initiates meta parameter optimisation. You choose the number of iterations that should run, which can be seen as the number of attempts the algorithm should make to find the optimal combination.

Fifty iterations usually give a combination set close to optimal without taking unduly long.

Please note that the maximum is 100 and the minimum is 5.

For more information, please refer to the API documentation.

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