diff --git a/report/main.pdf b/report/main.pdf deleted file mode 100644 index 8cd4705..0000000 Binary files a/report/main.pdf and /dev/null differ diff --git a/report/main.typ b/report/main.typ deleted file mode 100644 index afbe00b..0000000 --- a/report/main.typ +++ /dev/null @@ -1,14 +0,0 @@ -#import "@preview/touying:0.6.1": * -#import themes.simple: * - -#show: simple-theme.with(aspect-ratio: "16-9") - -= Title - -== First Slide - -Hello, Touying! - -#pause - -Hello, Typst! diff --git a/report/ntnu.png b/report/ntnu.png new file mode 100644 index 0000000..7e45f6b Binary files /dev/null and b/report/ntnu.png differ diff --git a/report/presentation.pdf b/report/presentation.pdf new file mode 100644 index 0000000..b55450d --- /dev/null +++ b/report/presentation.pdf @@ -0,0 +1,3045 @@ +%PDF-1.7 +% + +1 0 obj +<< + /Type /Pages + /Count 8 + /Kids [219 0 R 221 0 R 223 0 R 225 0 R 227 0 R 229 0 R 231 0 R 233 0 R] +>> +endobj + +2 0 obj +<< + /Type /Outlines + /First 3 0 R + /Last 9 0 R + 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505.99997 5 5 271 6 6 512 7 7 250 8 8 504 9 9 493 10 10 316 11 11 390 12 12 542 13 13 531 14 15 465 16 16 220 17 18 465 19 19 351 20 20 538 21 21 457 22 22 790 23 23 515 24 24 220 25 25 428 26 26 747 27 27 497 28 28 264 29 29 500 30 30 519 31 31 375 32 32 268 33 33 435 34 34 490 35 35 424 36 36 465 37 37 236 38 38 560 39 39 236 40 40 338 41 41 465 42 42 323 43 43 465 44 44 540 45 45 548 46 47 465] +>> +endobj + +192 0 obj +<< + /Length 11 + /Filter /FlateDecode +>> +stream +x +endstream +endobj + +193 0 obj +<< + /Type /FontDescriptor + /FontName /QYDRXO+LibertinusSerif-Regular + /Flags 131078 + /FontBBox [0 -238 782 698] + /ItalicAngle 0 + /Ascent 894 + /Descent -246 + /CapHeight 658 + /StemV 95.4 + /CIDSet 192 0 R + /FontFile3 195 0 R +>> +endobj + +194 0 obj +<< + /Length 1272 + /Type /CMap + /WMode 0 +>> +stream +%!PS-Adobe-3.0 Resource-CMap +%%DocumentNeededResources: procset CIDInit +%%IncludeResource: procset CIDInit +%%BeginResource: CMap Custom +%%Title: (Custom Adobe Identity 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Resource-CMap +%%DocumentNeededResources: procset CIDInit +%%IncludeResource: procset CIDInit +%%BeginResource: CMap Custom +%%Title: (Custom Adobe Identity 0) +%%Version: 1 +%%EndComments +/CIDInit /ProcSet findresource begin +12 dict begin +begincmap +/CIDSystemInfo 3 dict dup begin + /Registry (Adobe) def + /Ordering (Identity) def + /Supplement 0 def +end def +/CMapName /Custom def +/CMapVersion 1 def +/CMapType 0 def +/WMode 0 def +1 begincodespacerange +<0000> +endcodespacerange +18 beginbfchar +<0001> <0063> +<0002> <006F> +<0003> <006D> +<0004> <0062> +<0005> <0069> +<0006> <006E> +<0007> <0061> +<0008> <0074> +<0009> <0066> +<000A> <0065> +<000B> <0075> +<000C> <0072> +<000D> <0073> +<000E> <0070> +<000F> <0020> +<0010> <006C> +<0011> <0067> +<0012> <0076> +endbfchar +endcmap +CMapName currentdict /CMap defineresource pop +end +end +%%EndResource +%%EOF +endstream +endobj + +201 0 obj +<< + /Length 2617 + /Filter /FlateDecode + /Subtype /CIDFontType0C +>> +stream +x}U{PSWnĖ۬zo=nNmjZ߶>)*(&k 0 h6Jt}4w!q=æÞ M-~`Xo_(mMeRd%Y)IɲEeF,{y٫˖/ړ,Z8EQْTQlz,Yf`i]Uݩiwsb]R;g!b:l%lN`9짂aF=Sj3]\> Lj;AS3~76dyPM(wqܣ3iy;콑?Nr,''C,駨&W:pُw:3Q<%@ uDIR1+?8DMCK RcE_IQ.Vc3ج1šڦ $l +1k"TǁTYץ8Bevr&t*dxH(n_݇+ߢhjSmp[(6q`X! 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"16-9", + config-info( + title: [bioai - assignment 1], + author: [fredrik robertsen], + date: "09.02.2026", + institution: [ntnu idi], + logo: box(image("ntnu.png", height: 1em)) + ), +) + +#title-slide(authors: [fredrik robertsen]) + +== problem 1 - binary knapsack + +- there are many items, each with a value and weight +- the knapsack you are wearing can only carry so much weight +- you want the most bang for your buck + - what's the best _combination_ of items to keep? +- combinatory problem, np hard + - approximate using a genetic algorithm +- this is like optimizing your inventory in games like skyrim + - do you want 400 spoons in your pocket, each worth a dime, or do you want that gold bar that weighs a ton? +- formally, you want to maximize $z = sum_(j=1)^n p_j x_j$ such that $sum_(j=1)^n w_j x_j <= c$ where $x_j in {0, 1}$ + - for item $j$: $p_j$ is the profit; $w_j$ the weight; $x_j$ whether to keep it + +== problem 2 - feature selection + +- similar to the binary knapsack problem +- this time you have many data points + - each data point consists of _features_ +- each data point has an associated _output_ +- you wish to eliminate the features that are least influential in producing a given output + - this is like choosing what items to keep in your knapsack +- this is like weather forecasting + - hundreds of features in data + - which are most relevant? + - which are noise? + +== general implementation + +- generate a population of randomized chromosomes +- calculate their fitness values +- perform a _tournament selection_ to choose parent chromosomes + - more fit individuals are more likely to be selected + - introduces less diversity +- combine two parents to form two children via _single point crossover_ +- mutate children randomly +- merge children into population, evicting the least fit individuals + - this is the _elitism survivor selection_ +- repeat + +== specific implementation + +- fitness function + - used the sum mentioned earlier + - used linear regression and rmse for feature selection + +== optimizations + +todo + +== results + +todo + +== conclusion + +todo