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  2. t-distributed stochastic neighbor embedding - Wikipedia

    en.wikipedia.org/wiki/T-distributed_stochastic...

    While t-SNE plots often seem to display clusters, the visual clusters can be strongly influenced by the chosen parameterization (especially the perplexity) and so a good understanding of the parameters for t-SNE is needed. Such "clusters" can be shown to even appear in structured data with no clear clustering, [13] and so

  3. Poincaré plot - Wikipedia

    en.wikipedia.org/wiki/Poincaré_plot

    A Poincaré plot, named after Henri Poincaré, is a graphical representation used to visualize the relationship between consecutive data points in time series to detect patterns and irregularities in the time series, revealing information about the stability of dynamical systems, providing insights into periodic orbits, chaotic motions, and bifurcations.

  4. Spike-triggered average - Wikipedia

    en.wikipedia.org/wiki/Spike-triggered_average

    Let denote the spatio-temporal stimulus vector preceding the 'th time bin, and the spike count in that bin. The stimuli can be assumed to have zero mean (i.e., [] =).If not, it can be transformed to have zero-mean by subtracting the mean stimulus from each vector.

  5. Independent component analysis - Wikipedia

    en.wikipedia.org/wiki/Independent_component_analysis

    It is closely related to (or even a special case of) the search for a factorial code of the data, i.e., a new vector-valued representation of each data vector such that it gets uniquely encoded by the resulting code vector (loss-free coding), but the code components are statistically independent.

  6. Biplot - Wikipedia

    en.wikipedia.org/wiki/Biplot

    The transformed data matrix Y is obtained from the original matrix X by centering and optionally standardizing the columns (the variables). Using the SVD, we can write Y = Σ k =1,... p d k u k v k T ;, where the u k are n -dimensional column vectors, the v k are p -dimensional column vectors, and the d k are a non-increasing sequence of non ...

  7. Correlogram - Wikipedia

    en.wikipedia.org/wiki/Correlogram

    In the analysis of data, a correlogram is a chart of correlation statistics. For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram.

  8. Owen's T function - Wikipedia

    en.wikipedia.org/wiki/Owen's_T_function

    The function T(h, a) gives the probability of the event (X > h and 0 < Y < aX) where X and Y are independent standard normal random variables. This function can be used to calculate bivariate normal distribution probabilities [2] [3] and, from there, in the calculation of multivariate normal distribution probabilities. [4]

  9. Mean absolute error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_error

    The MAE is conceptually simpler and also easier to interpret than RMSE: it is simply the average absolute vertical or horizontal distance between each point in a scatter plot and the Y=X line. In other words, MAE is the average absolute difference between X and Y.

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