Decision Tree

The key is to make the program to learn from the data and generate a decision tree automatically. The approach is via supervised learning with label data sets. It took effort but can benefits others when the learning is completed.  

Detecting error only in transmission

(1) simple checksum - calculate a checksum based on the text. This can detect one error but not two and above. It is because 2 error can result in the same checksum  

(2) staircase checksum is calculated by multiplying each byte with a sequence number and then take the checksum of the text. Using simple checksum and staircase checksum together can detect 2 errors in the text. When one or both checksum cannot be matched, it indicated there could be 1 or 2 errors. 

Detecting and correcting error in transmission

(1) retransmit multiple times (based on the error rate if the line) and for each byte, pick the pattern that appear most. Based on probability, the right pattern would be picked but there is no guarantee. 

(2) encode each byte with additional bits. The received bits can match against the encoding pattern.  The closest matching pattern is the transmitted byte. This is how hamming code works. 

(3) two dimensional parity ones the text in 2 dimensional block. Then take a checksum across the row and down the column. This allows to pinpoint the byte that has changed (error). The byte can be recomputed from the vertical and horizontal checksum. In reverse.