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Scala Machine Learning Projects

You're reading from   Scala Machine Learning Projects Build real-world machine learning and deep learning projects with Scala

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788479042
Length 470 pages
Edition 1st Edition
Languages
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Author (1):
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Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
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Toc

Table of Contents (13) Chapters Close

Preface 1. Analyzing Insurance Severity Claims FREE CHAPTER 2. Analyzing and Predicting Telecommunication Churn 3. High Frequency Bitcoin Price Prediction from Historical and Live Data 4. Population-Scale Clustering and Ethnicity Prediction 5. Topic Modeling - A Better Insight into Large-Scale Texts 6. Developing Model-based Movie Recommendation Engines 7. Options Trading Using Q-learning and Scala Play Framework 8. Clients Subscription Assessment for Bank Telemarketing using Deep Neural Networks 9. Fraud Analytics Using Autoencoders and Anomaly Detection 10. Human Activity Recognition using Recurrent Neural Networks 11. Image Classification using Convolutional Neural Networks 12. Other Books You May Enjoy

Predicting prices and evaluating the model

ShortTermPredictionServiceImpl is the class that actually performs the prediction with the given model and data. At first, it transforms PriceData into a Spark DataFrame with the scheme corresponding to the one used for training by calling transformPriceData(priceData: PriceData). Then, the model.transform(dataframe) method is called; we extract the variables we need, write into the debugger log and return to the caller:

override def predictPriceDeltaLabel(priceData: PriceData, mlModel: org.apache.spark.ml.Transformer): (String, Row) = {
val df = transformPriceData(priceData)
val prediction = mlModel.transform(df)
val predictionData = prediction.select("probability", "prediction", "rawPrediction").head()
(predictionData.get(1).asInstanceOf[Double].toInt.toString, predictionData...
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