und 5€ an der Abendkasse.**// * //**Ihr wollt helfen?**// [[https://doodle.com/poll/kse23skcep2pvggy|Doodle]] [2], <matthias.schaffartzik@tu-dortmund.de> \\ ------------------- //Falls die Links im Fließtext [...] Ihr sie noch einmal hier:// \\ [1] https://fsinfo.cs.tu-dortmund.de/fsr/sitzung \\ [2] https://doodle.com/poll/kse23skcep2pvggy \\ …

Distance Functions – Lecture Notes

Distance Functions /2 Many more variants: Squared Euclidean distance ( sum of squares ): \[\begin{align*} d_{\operatorname {Euclidean}}^2(x,y) =& \kern 5pt \sum \nolimits _d (x_d - y_d)^2 \quad = \left\lVert [...] y\right\rVert } = \tfrac { \sum _i x_i y_i }{ \sqrt{\sum _i x_i^2} \cdot \sqrt{\sum _i y_i^2} }\] only (!) on data normalized to \(L_2\) length \(\left\lVert x\right\rVert =\left\lVert y\right\rVert =1\) [...] where \(o_1\) has 1 and \(o_2\) has 0 \(f_{00}\) = the number of attributes where \(o_1\) has 0 and \(o_2\) has 0 \(f_{11}\) = the number of attributes where \(o_1\) has 1 and \(o_2\) has 1 Simple matching …

Distance Functions – Lecture Notes

Distance Functions /2 Many more variants: Squared Euclidean distance ( sum of squares ): \[\begin{align*} d_{\operatorname {Euclidean}}^2(x,y) =& \kern 5pt \sum \nolimits _d (x_d - y_d)^2 \quad = \left\lVert [...] y\right\rVert } = \tfrac { \sum _i x_i y_i }{ \sqrt{\sum _i x_i^2} \cdot \sqrt{\sum _i y_i^2} }\] only (!) on data normalized to \(L_2\) length \(\left\lVert x\right\rVert =\left\lVert y\right\rVert =1\) [...] where \(o_1\) has 1 and \(o_2\) has 0 \(f_{00}\) = the number of attributes where \(o_1\) has 0 and \(o_2\) has 0 \(f_{11}\) = the number of attributes where \(o_1\) has 1 and \(o_2\) has 1 Simple matching …