Probabilistic models are commonly used to model various forms of data, including physical, biological, seismic, etc. Much of their popularity can be attributed to the existence of efficient and robust procedures for learning parameters from observations. Often, however, the only data available for training a probabilistic model are incomplete. Missing values can occur which will not be sufficient to get the model. For example, in medical diagnosis, patient histories generally include results from a limited battery of tests. In gene expression clustering, incomplete data arise from the intentional omission of gene-to-cluster assignments in the probabilistic model. If we use regular techniques to estimate the underlying model, then we will get a wrong estimate. What do we do in these situations? Continue reading

# Tag Archives: Distribution

# Reimann Hypothesis And Its Connection To Cryptography

Over the centuries, mathematicians have been involved in solving some of most complex problems. But what is the motivation behind that? The pursuit of truth! But The Clay Mathematics Institute thought that there should be a little more than that. So to celebrate mathematics in the new millennium, they established seven Millennium Prize Problems. The prize money for each problem is one million dollars. That’s pretty exciting! These were some of the most difficult problems over which many mathematicians were racking their brains. Reimann Hypothesis is one of them. The interesting thing about this particular problem is that it has far reaching consequences in the field of modern cryptography and internet security. Now how can an obscure and complex mathematical problem affect cryptography and internet security? Continue reading

# The Butterfly Effect

This blog post is a continuation of my previous post on Chaos Theory. Although it is not required for you to read that post to understand this post, it would be better if you glance through it once. All of us have heard about the Butterfly Effect. It is one of the very famous examples given in the field of chaos theory. I should also give credit to the movie “The Butterfly Effect” for popularizing this term. So what exactly is butterfly effect? Is it just a theory? Where does it happen in real life? Continue reading

# Chaos Theory

Chaos Theory is a mathematical sub-discipline that attempts to explain the fact that complex and unpredictable results can and will occur in systems that are sensitive to their initial conditions. Some common examples of systems that chaos theory helped understand are earth’s weather system, the behavior of water boiling on a stove, migratory patterns of birds, or the spread of vegetation across a continent. The Butterfly Effect is one of more famous examples of chaos theory. I have discussed more about it here. Chaos occurs in nature and it manifests itself in various forms. Chaos-based graphics show up all the time, wherever flocks of little space ships sweep across the movie screen in highly complex ways, or whenever amazing landscapes are displayed in some dramatic movie scene. It is used a lot in movies to generate obscure background using computer-generated chaos art. So what exactly is chaos? How does it work? Continue reading

# Interpretation of Gaussian Distribution

When we deal with large amount of data, we can’t have specific rules for each and every instance. We have to come up with a model which defines the whole data. This model can then be used to analyze unknown inputs. More often than not, the data has some underlying pattern. When we think of a model, we extract specific characteristics from the data and come up with a formulation which best explains the behavior of the data. One of the most frequently occurring pattern is the Gaussian Distribution. It is used almost everywhere in science and technology. But what is it exactly? Why do we need it? Continue reading

# Probabilistic Randomness Of Stochasticity

Do you see what I did with the title there? Anyway, you must have heard the term ‘probability’ being used around you. People use it in different contexts and in different forms – “What is the *probability* that Spain will win the next world cup?” or “I will *probably* finish reading the book by midnight” or “It’s quite *probable* that she won’t return until tomorrow”. When people talk about probability as a mathematical concept, all they think of is the percentage chance of something happening. But is that all there is to it? If that is the case, then why did they have to dedicate an entire branch of study to this? Probability theory is much more than just calculating the likeliness of something happening. It’s used almost everywhere, by almost everyone, for almost everything. Surprised? Well let’s find out then. Continue reading