ML Scatter Plots

• Data Collections
• Scatter Plots
• Graphs

Data Collection

Collecting data is the most important part of any Machine Intelligence projects.

The most common data to collect are numbers and measurements.

Often data are stored in arrays representing the relationship between values.

This table contains house prices versus size:

Scatter Plots

A Scatter Plot has points scattered over an area representing the relationship between two values.

Example

const xArray = [50,60,70,80,90,100,110,120,130,140,150];
const yArray = [7,8,8,9,9,9,10,11,14,14,15];

// Define Data
const data = [{
  x: xArray,
  y: yArray,
  mode:"markers"
}];

// Define Layout
const layout = {
  xaxis: {range: [40, 160], title: "Square Meters"},
  yaxis: {range: [5, 16], title: "Price in Millions"},
  title: "House Prices vs. Size"
};

// Display with Plotly
Plotly.newPlot("myPlot", data, layout);

Graphs

A Graph can also be used to show the same values:

Source Code

const xArray = [50,60,70,80,90,100,110,120,130,140,150];
const yArray = [7,8,8,9,9,9,10,11,14,14,15];

// Define Data
const data = [{
  x: xArray,
  y:yArray,
  mode:"lines"
}];

// Define Layout
const layout = {
  xaxis: {range: [40, 160], title: "Square Meters"},
  yaxis: {range: [5, 16], title: "Price in Millions"},
  title: "House Prices vs Size"
};

// Display with Plotly
Plotly.newPlot("myPlot", data, layout);

When to Use Scatter Plots

Scatter plots are great for:

• Seeing the "Big Picture"
• Compare different values
• Discovering potential trends
• Discovering patterns in data
• Discovering relationships between data
• Discovering Clusters and Correlations