private static async Task Main(string[] args)
{
var model = Train();
BookData t1 = new BookData
{
genre = 5.1f,
releaseTime = 3.5f,
price = 1.4f,
};
var prediction = model.Predict(t1);
}
private static PredictionModel <BookData, ClusterPrediction> Train()
{
var pipeline = new LearningPipeline();
// pipeline.Add(new TextLoader(_dataPath).CreateFrom<BookData>(separator: ','));
//building dataset of BookData
List <BookData> data = new List <BookData>();
string line;
using (var reader = File.OpenText(_dataPath))
{
while ((line = reader.ReadLine()) != null)
{
string convertedData = line;
List <string> BookFeaturesSet = convertedData.Split(',').ToList();
BookData bd = new BookData
{
genre = float.Parse(BookFeaturesSet[0]), //book.Genre,
releaseTime = float.Parse(BookFeaturesSet[1]),
price = float.Parse(BookFeaturesSet[2]) //book.Price
};
data.Add(bd);
}
}
var collection = CollectionDataSource.Create(data);
pipeline.Add(collection);
pipeline.Add(new ColumnConcatenator(
"Features",
"price",
"genre",
"releaseTime")
);
pipeline.Add(new KMeansPlusPlusClusterer()
{
K = 5
});
var model = pipeline.Train <BookData, ClusterPrediction>();
return(model);
}
public ClusterPrediction Predict(BookData bookData)
{
var model = Train();
return(model.Predict(bookData));
}