First draft of Linear Regression

First draft

Author: james-mux

Linear Regression/LinearRegression.playground/Contents.swift

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+// Linear Regression
+
+import Foundation
+
+let carAge: [Double] = [10, 8, 3, 3, 2, 1]
+let carPrice: [Double] = [500, 400, 7000, 8500, 11000, 10500]
+var intercept = 10000.0
+var slope = -1000.0
+let alpha = 0.0001
+let numberOfCarAdvertsWeSaw = carPrice.count
+
+func h(carAge: Double) -> Double {
+    return intercept + slope * carAge
+}
+
+for n in 1...10000 {
+    for i in 1...numberOfCarAdvertsWeSaw {
+        intercept += alpha * (carPrice[i-1] - h(carAge[i-1])) * 1
+        slope += alpha * (carPrice[i-1] - h(carAge[i-1])) * carAge[i-1]
+    }
+}
+
+print("A car age 4 years is predicted to be worth £\(Int(h(4)))")

Linear Regression/LinearRegression.playground/contents.xcplayground

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+<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
+<playground version='5.0' target-platform='ios'>
+    <timeline fileName='timeline.xctimeline'/>
+</playground>

Linear Regression/LinearRegression.playground/playground.xcworkspace/contents.xcworkspacedata

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+# Linear Regression
+## First draft version of this document
+
+Linear regression is a technique for creating a model of the relationship between two (or more) variable quantities.
+
+For example, let's say we are planning to sell a car. We are not sure how much money to ask for. So we look at recent advertisments for the asking prices of other cars. There are a lot of variables we could look at - for example: make, model, engine size. To simplify our task, we collect data on just the age of the car and the price:
+
+Age (in years)| Price (in £)
+--------------|-------------
+10 | 500
+8 | 400
+3 | 7,000
+3 | 8,500
+2 | 11,000
+1 | 10,500
+
+Our car is 4 years old. How can we set a price for our car based on the data in this table?
+
+*Written for Swift Algorithm Club by James Harrop*