You gave me code though instead of an answer in natural language. Anyhow, the most basic pattern in all datasets is this, used to predict data based on context (it's powerful and allows/builds all the rest of the AI abilities): Every time you see the context 'cat', store what letter was to the right of it. You'll learn a probability distribution ex. usually the letter to the right is a s, sometimes b, rarely p, ex. cat>s=0.45% likely, t=0.22% likely..etc....you get these from gathering counts of each possible letter, then using the total sum to get percentages. This tells you for some context of #letters what the next letter probably is.
I need simple explanations like this... ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T5b614d3e3bb8e0da-Ma4eacb7de452f433cb2a5ba7 Delivery options: https://agi.topicbox.com/groups/agi/subscription
