Question

Consider a binary classifier and Gaussian conditional distribution, with mean and covariance matrix. Find the decision boundary. More details below.

score 1.5k · Answer 1 · 2026-03-25 03:07:49

1.5k

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Consider a binary classifier and Gaussian conditional distribution, with mean and covariance matrix. Find the decision boundary. More details below.

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score 281 · Answer 2 · 2018-03-30 00:38:55

281

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score 450 · Answer 3 · 2018-03-30 10:35:13

450

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score 69 · Answer 6 · 2018-03-31 23:58:38

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score 1.4k · Answer 7 · 2026-03-26 22:14:12

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score 261 · Answer 13 · 2018-04-04 04:59:34

261

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Finding $P(X_1+X_2 > 1.9X_3)$ where $X_1$, $X_2$, and $X_3$ are independent, normal distributed random variables

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73

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score 57 · Answer 15 · 2018-04-04 17:11:02

57

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What's the distribution of $(n_1+n_2+n_3)/\sqrt{N_1N_2N_3}$ with $n_i$ running from $0$ to $N_i - 1$

Published on 04 Apr 2018 - 17:11

List Question

Consider a binary classifier and Gaussian conditional distribution, with mean and covariance matrix. Find the decision boundary. More details below.

Deriving the distribution of Random variable

Evaluating $\int_0^\infty\Phi\left(\frac{\ln x-\mu}{\sigma}\right)\left(1-\Phi\left(\frac{\ln x-\mu}{\sigma}\right)\right)\mathrm{d}x$

Feasible region of probabilistic constraint

Theoretical variance of a sum of random variables

How can I impute missing values in data such that the end result is close to normal?

Finding $v_{rms}$ of a gas molecule using Maxwell-Boltzmann distribution

Why variance in kalman?

Partial average of normal distribution

How to find posterior distribution of some parameters for a model of the standard deviation for Gauss distributed data?

Expectation of product of bivariate normal distribution

MLE for normal distribution

Finding $P(X_1+X_2 > 1.9X_3)$ where $X_1$, $X_2$, and $X_3$ are independent, normal distributed random variables

calculate critical value from confidence level - hypothesis testing

What's the distribution of $(n_1+n_2+n_3)/\sqrt{N_1N_2N_3}$ with $n_i$ running from $0$ to $N_i - 1$

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