# Questions tagged [statistics]

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### Applying Expectation Maximization to coin toss examples

I've been self-studying the Expectation Maximization lately, and grabbed myself some simple examples in the process: From here: There are three coins $c_0$, $c_1$ and $c_2$ with $p_0$, $p_1$ and $p_2$...
• 345
274 views

### How best to statistically verify random numbers?

Lets say I have 1000 bytes that are supposedly random. I want to verify to a certain certainty that they are indeed random and evenly distributed across all byte values. Aside from calculating the ...
• 73
384 views

### Applying graph "adjustment" algorithms to Elo rating system

I'm trying to address what I perceive to be a potential shortcoming in the Elo Rating System (predominantly used by the international Chess community to rate + rank players). I have a two-player game ...
• 153
202 views

### Redistributing a set of uniformly distributed numbers to an arbitrarily defined shape

Lets say I have a random number generator that spits out uniform numbers from 0 to 1 Next, I have a shape defined by a series of vertices, like { [0, 0.4], [0.5, 0.2], [1, 0.4] } In those vertices, ...
• 131
944 views

### Predicting energy consumption of households

I have the dataset which you can find here, containing many different characteristics of different houses, including their types of heating, or the number of adults and children living in the house. ...
10k views

I've studied this lots, and they say overfitting the actions in machine learning is bad, yet our neurons do become very strong and find the best actions/senses that we go by or avoid, plus can be de-...
8k views

### Showing that Bayes classifier is optimal

Consider domain $X$, label set $Y=\{0,1\}$ and the zero-one loss. Given any probability distribution D over $X\times \{0,1\}$, we've defined the Bayes classifier $f_D$ to be-  f_{D}(x)= \...
• 215
3k views

### What would be a decent threshold for classification problem?

I'm using machine-learning algorithms to solve binary classification problem (i.e. classification can be 'good' or 'bad'). I'm using SVM based algorithms, ...
• 133