diff --git a/DSD/qrs/presentation/images/2d_p1.svg b/DSD/qrs/presentation/images/2d_p1.svg new file mode 100644 index 0000000..511156e --- /dev/null +++ b/DSD/qrs/presentation/images/2d_p1.svg @@ -0,0 +1,97 @@ + + + + diff --git a/DSD/qrs/presentation/images/2d_p2.svg b/DSD/qrs/presentation/images/2d_p2.svg new file mode 100644 index 0000000..b1c7994 --- /dev/null +++ b/DSD/qrs/presentation/images/2d_p2.svg @@ -0,0 +1,163 @@ + + + + diff --git a/DSD/qrs/presentation/images/2d_p3.svg b/DSD/qrs/presentation/images/2d_p3.svg new file mode 100644 index 0000000..cf48c33 --- /dev/null +++ b/DSD/qrs/presentation/images/2d_p3.svg @@ -0,0 +1,206 @@ + + + +P1P2P3 diff --git a/DSD/qrs/presentation/images/2d_p4.svg b/DSD/qrs/presentation/images/2d_p4.svg new file mode 100644 index 0000000..8d112d8 --- /dev/null +++ b/DSD/qrs/presentation/images/2d_p4.svg @@ -0,0 +1,219 @@ + + + +P1P2P3 diff --git a/DSD/qrs/presentation/images/2d_p5.svg b/DSD/qrs/presentation/images/2d_p5.svg new file mode 100644 index 0000000..c86f8fb --- /dev/null +++ b/DSD/qrs/presentation/images/2d_p5.svg @@ -0,0 +1,182 @@ + + + +P1P2P3 diff --git a/DSD/qrs/presentation/images/2d_p6.svg b/DSD/qrs/presentation/images/2d_p6.svg new file mode 100644 index 0000000..58ae427 --- /dev/null +++ b/DSD/qrs/presentation/images/2d_p6.svg @@ -0,0 +1,182 @@ + + + +P1P2P3 diff --git a/DSD/qrs/presentation/images/2d_view.svg b/DSD/qrs/presentation/images/2d_view.svg new file mode 100644 index 0000000..35ae60e --- /dev/null +++ b/DSD/qrs/presentation/images/2d_view.svg @@ -0,0 +1,1072 @@ + + + +P1P2P3P1P2P3P1P2P3P1P2P3 diff --git a/DSD/qrs/presentation/presentation.typ b/DSD/qrs/presentation/presentation.typ index 6195d2c..ada63ea 100644 --- a/DSD/qrs/presentation/presentation.typ +++ b/DSD/qrs/presentation/presentation.typ @@ -51,21 +51,33 @@ #align(center)[ #text(weight: "bold")[Metric:] The distance between a sample and a pattern is the minimum normalized distance between the pattern and any pattern-length substring that includes the samples. #v(1cm) -#text(weight: "bold")[Decision:] Every sample is receives the label of the closest training pattern. +#text(weight: "bold")[Decision:] Each sample receives the label of the closest training pattern. ] ] - -#slide(title: "Proposed Approach - 2D Interpretation")[ - #figure( - image("images/overview.svg", height: 100%) - ) +#slide(title: "2D Interpretation")[ + + #only(1)[#figure(image("images/2d_p1.svg", width: 100%))] + #only(2)[#figure(image("images/2d_p2.svg", width: 100%))] + #only(3)[#figure(image("images/2d_p3.svg", width: 100%))] + #only(4)[#figure(image("images/2d_p4.svg", width: 100%))] + #only(5)[#figure(image("images/2d_p5.svg", width: 100%))] ] -#slide(title: "Proposed Approach - 2D Interpretation")[ +#slide(title: "Question")[ +#align(center)[Should the algorithm #text(weight: "bold")[always] choose a label?] +] + +#slide(title: "2D Interpretation")[ + + #figure(image("images/2d_p6.svg", width: 100%)) +] + +#slide(title: "Parameter "+sym.alpha)[ #figure( image("images/areas.svg", width: 100%) ) +#align(center)[With $alpha lt.triple 2$, the algorithm acquire novelty-detection capability.] ] #slide(title: "Parameter")[]