AI

 Predict and Recall:

Self example:

Okay Assume in next month you predict that every saturday it will rain.

In this example: If it rains for 2 saturday then prediction is 50%(i.e 2/4 = 50%)

Recall is another view point and observing at the finish of predicted month and seeing if it rained other than saturday.

The it rained one Monday in the month then that is missed to be predicted.

So calcultation of recall is (2/(2predicted correctly+1 missed)) system found 2/3 = 75% the system is 75% capable to find the happenings.

ChatGPT ex:

Absolutely, I can explain precision and recall in the context of stock market predictions.

Imagine you're developing a system that predicts whether a stock will go up (positive) or down (negative) tomorrow. Precision and recall can help you measure how accurate your predictions are.

1. Precision for Stocks: Precision here would be the ratio of correctly predicted "up" days to all the days your system predicted as "up." In other words, it's about how often your system's "up" predictions are actually correct.

   High precision means that when your system predicts a stock will go up, it's often right.

2. Recall for Stocks: Recall would be the ratio of correctly predicted "up" days to all the actual "up" days. In other words, it's about how many of the actual "up" days your system managed to predict correctly.

   High recall means that your system is good at capturing most of the actual "up" days.

Here's a simple example:

Let's say your system predicted 20 "up" days. Out of those, 15 days actually went up (true positives), and 5 days went down (false positives). Additionally, there were 10 more "up" days that your system missed (false negatives).

• Precision: Out of the 20 days your system predicted as "up," 15 actually went up. So, precision = 15 / 20 = 0.75 or 75%.
• Recall: Out of the 25 total "up" days (15 correctly predicted + 10 missed), your system found 15. So, recall = 15 / 25 = 0.6 or 60%.

In the stock context, precision is about not making too many false predictions when saying the stock will go up, while recall is about not missing out on many actual "up" days. It's a trade-off, as improving precision might decrease recall and vice versa. The goal is to find a balance that fits your investment strategy and risk tolerance.