Unconditional Probability  Python Automation and Machine Learning for ICs   An Online Book  

Python Automation and Machine Learning for ICs http://www.globalsino.com/ICs/  


Chapter/Index: Introduction  A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  Appendix  
================================================================================= In machine learning, different from conditional probability, unconditional probability refers to the probability of an event occurring without any conditions or prior knowledge. It is often denoted as P(A), where A is the event in question. Unconditional probability provides a straightforward measure of the likelihood of an event happening, regardless of other factors. Unconditional probability is a fundamental concept in probability theory and is used in various machine learning algorithms, particularly in tasks related to probability estimation, classification, and decisionmaking. Mathematically, the unconditional probability of an event A is calculated as the ratio of the number of favorable outcomes for A to the total number of possible outcomes in the sample space. The formula is:  [3618a]
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