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Update click_train_help.md

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Jamie Mac 2022-02-18 08:52:28 +00:00
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src/clickTrainDetector/click_train_help.md
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@ -60,7 +60,7 @@ The initial basis of the model is:
where _m_ is the number of selected descriptors, e.g. ICI, amplitude, bearing etc., and _y(i,k)_ is the measurement of descriptor _i_ for click _k_ in a click train with n associated clicks. _t(k+1)_ is the measured time of a click _k_. Each descriptor is divided by q<sub>i</sub> which is a user tuneable parameter that alters the importance each descriptor has on the total χ<sup>2</sup>. Ideally it should correspond to a prediction of the likely variance of the descriptor. where _m_ is the number of selected descriptors, e.g. ICI, amplitude, bearing etc., and _y(i,k)_ is the measurement of descriptor _i_ for click _k_ in a click train with n associated clicks. _t(k+1)_ is the measured time of a click _k_. Each descriptor is divided by q<sub>i</sub> which is a user tuneable parameter that alters the importance each descriptor has on the total χ<sup>2</sup>. Ideally it should correspond to a prediction of the likely variance of the descriptor.
The descriptors can be enabled and the variance set in the χ<sup>2</sup> Settings pane. The toggle button next to each descriptor sets whether a descriptor is used to score a click train and the variance is then set using the slider or by inputting manually by clicking the settings cog. Increasing the variance means that the descriptor has less of an influence on the calculation of χ<sup>2</sup> and decreasing means that the descriptor has a larger influence on χ<sup>2</sup>. In some cases, clicks can be so close together that the variance is tiny and thus χ<sup>2</sup> becomes huge e.g. during buzzes. A minimum variance value (〖qt〗_i) prevents the variance _(〖max⁡(q<sub>i</sub> (t(k+1)-t_k ),〖qt〗_i )〗<sup>2</sup>)_ from falling below very low values. The descriptors can be enabled and the variance set in the χ<sup>2</sup> Settings pane. The toggle button next to each descriptor sets whether a descriptor is used to score a click train and the variance is then set using the slider or by inputting manually by clicking the settings cog. Increasing the variance means that the descriptor has less of an influence on the calculation of χ<sup>2</sup> and decreasing means that the descriptor has a larger influence on χ<sup>2</sup>. In some cases, clicks can be so close together that the variance is tiny and thus χ<sup>2</sup> becomes huge e.g. during buzzes. A minimum variance value (_qt<sub>i</sub>_) prevents the variance _(max⁡(q<sub>i</sub> (t<sub>(k+1)</sub>-t<sub>k</sub> ),qt<sub>i</sub> )<sup>2</sup>)_ from falling below very low values.
Ideally the variance for each parameter would be calculated from a test dataset of manually annotated click trains e.g. by calculating the variance of ICI of all marked click trains. Ideally the variance for each parameter would be calculated from a test dataset of manually annotated click trains e.g. by calculating the variance of ICI of all marked click trains.