MissingNo.

Analysis of generated potential Pokemon based on types, routes, nature, encounter rates, time of day, level etc. to be used in future models of predictive ML and predictions.

We are starting with Kanto as out build test.

Table of Contents

• Scope
• Goals
• Questions

Scope

Using Kanto data for now.

Goals

1. Build base for generating Pokemon for ML predictions and analysis

Questions

• What is the distribution of Pokemon across the region? based on Routes?
• What is the spread of Pokemon potentially available to catch in the wild? How does that potential look on each route?
• What is the percentage of encouter for given sets of Pokemon with possible parameters?

Data

Kanto pokemon data which would include:

• Pokemon Base Stats
• Types
• Route Information (encounter percentage, levels)
• Gender Types
• Natures
• IV
• Items

Analysis