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Tools : Statistics : Analysis : Forgetting Curves graphs for 20 repetition number categories multiplied by 20 A-Factor categories
{{Fig|'''[[Toolkit menu|Toolkit]] : [[Toolkit menu#Statistics|Statistics]] : [[Analysis]] : [[Analysis#Forgetting (UF)|Forgetting (UF)]]''' for 20 repetition number categories multiplied by 20 A-Factor categories. In the picture, <span style{{=}}"padding: 3px; color: #fff; background: blue;">blue circles</span> represent data collected during repetitions. The larger the circle, the greater the number of repetitions recorded. The <span style{{=}}"padding: 3px; color: #fff; background: red;">red curve</span> corresponds with the best-fit [[Glossary:Forgetting_curve|forgetting curve]] obtained by exponential regression. For ill-structured material the [[Glossary:Forgetting_index|forgetting curve]] is crooked, i.e. not exactly exponential. The horizontal <span style{{=}}"padding: 3px; background: aqua;">aqua line</span> corresponds with the [[Glossary:Requested_forgetting_index|requested forgetting index]], while the vertical <span style{{=}}"padding: 3px; color: #fff; background: green;">green line</span> shows the moment in time in which the approximated [[Glossary:Forgetting_curve|forgetting curve]] intersects with the requested forgetting index line. This moment in time determines the value of the relevant [[Glossary#R-Factor|R-Factor]], and indirectly, the value of the [[Glossary:Optimum_interval|optimum interval]]. For the first repetition, [[Glossary:R-Factor|R-Factor]] corresponds with the first [[Glossary:Optimum_interval|optimum interval]]. The values of [[Glossary:O-Factor|O-Factor]] and [[Glossary:R-Factor|R-Factor]] are displayed at the top of the graph. They are followed by the number of repetition cases used to plot the graph (i.e. 21,303). At the beginning of the learning process, there is no repetition history and no repetition data to compute [[Glossary:R-Factor|R-Factors]]. It will take some time before your first [[Glossary:Forgetting_curve|forgetting curves]] are plotted. For that reason, the initial value of the [[Glossary:RF_matrix|RF matrix]] is taken from the model of a less-than-average student. The model of average student is not used because the convergence from poorer student parameters upwards is faster than the convergence in the opposite direction. The '''Deviation''' parameter displayed at the top tells you how well the negatively exponential curve fits the data. The lesser the deviation, the better the fit. The deviation is computed as a square root of the average of squared differences (as used in the method of least squares).}}

Latest revision as of 03:46, 14 March 2019

Figure: Toolkit : Statistics : Analysis : Forgetting (UF) for 20 repetition number categories multiplied by 20 A-Factor categories. In the picture, blue circles represent data collected during repetitions. The larger the circle, the greater the number of repetitions recorded. The red curve corresponds with the best-fit forgetting curve obtained by exponential regression. For ill-structured material the forgetting curve is crooked, i.e. not exactly exponential. The horizontal aqua line corresponds with the requested forgetting index, while the vertical green line shows the moment in time in which the approximated forgetting curve intersects with the requested forgetting index line. This moment in time determines the value of the relevant R-Factor, and indirectly, the value of the optimum interval. For the first repetition, R-Factor corresponds with the first optimum interval. The values of O-Factor and R-Factor are displayed at the top of the graph. They are followed by the number of repetition cases used to plot the graph (i.e. 21,303). At the beginning of the learning process, there is no repetition history and no repetition data to compute R-Factors. It will take some time before your first forgetting curves are plotted. For that reason, the initial value of the RF matrix is taken from the model of a less-than-average student. The model of average student is not used because the convergence from poorer student parameters upwards is faster than the convergence in the opposite direction. The Deviation parameter displayed at the top tells you how well the negatively exponential curve fits the data. The lesser the deviation, the better the fit. The deviation is computed as a square root of the average of squared differences (as used in the method of least squares).

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current10:29, 2 April 2016Thumbnail for version as of 10:29, 2 April 20161,207 × 821 (158 KB)SuperMemoHelp (talk | contribs)
09:20, 27 July 2013Thumbnail for version as of 09:20, 27 July 20131,016 × 721 (147 KB)SuperMemoHelp (talk | contribs)Reverted to version as of 13:16, 27 July 2013
05:17, 24 April 2009Thumbnail for version as of 05:17, 24 April 2009936 × 650 (128 KB)WikiSysop (talk | contribs)Tools : Statistics : Analysis : Forgetting Curves graphs for 20 repetition number categories multipled by 20 A-Factor categories

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