Calculate the root mean square error of the two models using the RegressionEvaluator method.
- [Speaker] An important part about machine learning…is testing how we're doing, how accurate we are.…And so we're going to look now at evaluating…a linear regression model.…First, we're going to import the ML evaluation library,…then we're choose a metric,…and then we're going to calculate that metric.…In this case, we'll use the…root-mean-squared error, the RMSE.…Here in Databricks, I have the exercise file…4.4 evaluating the linear regression model loaded.…I need to attach this to my cluster,…then I need to go through and execute these first few…steps here, just to make sure that I have my data loaded,…everything's ready to go.…
So I'll just go click through play all of these…until I get down to the check models for accuracy.…So once that's done, I need to import the…evaluation library, so the pyspark.ml.evaluation,…and we're going to import regression evaluator.…We then need to choose the metric here, the RMSE,…as I mentioned, and we're going to actually…evaluate the results.…So we're going to run the RMSE here,…
- Understanding Spark
- Reviewing Spark components
- Where Spark shines
- Understanding data interfaces
- Working with text files
- Loading CSV data into DataFrames
- Using Spark SQL to analyze data
- Running machine learning algorithms using MLib
- Querying streaming data
- Connecting BI tools to Spark
Skill Level Intermediate
1. Introducing Apache Spark
2. Analyzing Data in Spark
3. Using Spark SQL to Analyze Data
4. Running Machine Learning Algorithms Using MLlib
5. Real-Time Data Analysis with Spark Streaming
6. Connecting BI Tools to Spark
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