scala.primer.scala

BigDecimal(1.002).setScale(2, BigDecimal.RoundingMode.HALF_UP).doubleValue() // Round double to #.##

| **Spark Term**                                               | **Description**                                              |
| ------------------------------------------------------------ | ------------------------------------------------------------ |
| Spreadsheet                                                  | Think of data as spreadsheet                                 |
| Statistical learning                                         | Output = f(input) # => f(inputVariable) or f(inputVector), or f(independent variables) or Y = F(X) // X1,X2,.. |
| Programming learning                                         | OutputAttributes = Program(InputAttributes) or Program(InputFeatures) or Model = Algorithm(Data) |
| Error                                                        | Y = f(X) + e # => You learn a function!                      |
| Parametric learning                                          | No matter how much data you throw on it, it will still need these parameters like a line Y = ax + b (logistic regression, linear discriminant analysis, perceptron) |