# Introduction

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PHP implementation of the (Weighted Slopeone,Cosine, Weighted Cosine) rating-based collaborative filtering schemes.

## Usage

OpenCF Package is designed to be very simple and straightforward to use. All you have to do is:

1. Load a training set (dataset)
2. Predict future ratings using a recommender. (Weighted Slopeone,Cosine, Weighted Cosine)

### Create Recommender Service

The `OpenCF` recommender service is created by direct instantiation:

```php
use OpenCF\RecommenderService;

// Training Dataset
$dataset = [
    "squid" => [
        "user1" => 1,
        "user2" => 1,
        "user3" => 0.2,
    ],
    "cuttlefish" => [
        "user1" => 0.5,
        "user3" => 0.4,
        "user4" => 0.9,
    ],
    "octopus" => [
        "user1" => 0.2,
        "user2" => 0.5,
        "user3" => 1,
        "user4" => 0.4,
    ],
    "nautilus" => [
        "user2" => 0.2,
        "user3" => 0.4,
        "user4" => 0.5,
    ],
];

// Create a recommender service instance
$recommenderService = new RecommenderService($dataset);

// Retrieve a recommender (Weighted Slopeone)
$recommender = $recommenderService->weightedSlopeone();

// Predict future ratings
$results = $recommender->predict([
    "squid" => 0.4
]);
```

This should produce the following results:

```php
[
  "cuttlefish" => 0.25,
  "octopus" => 0.23,
  "nautilus" => 0.1
];
```