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MDS

notebooks/mds.livemd

MDS

Mix.install([
  {:scholar, github: "elixir-nx/scholar", override: true},
  {:kino, "~> 0.11.3", override: true},
  {:kino_vega_lite, "~> 0.1.9"},
  {:exla, "~> 0.6.4"},
  {:tucan, "~> 0.3.0"},
  {:explorer, "~> 0.7.1"},
  {:req, "~> 0.4.5"},
  {:nx, git: "https://github.com/elixir-nx/nx.git", sparse: "nx", override: true}
])

Setup

alias Scholar.Manifold.MDS
alias VegaLite, as: Vl
alias Explorer.DataFrame, as: DF

Swiss Roll

The first example demonstrating MDS will use so-called Swiss Roll dataset. It’s call as such because it resembles a popular sponge cake. Let’s have a look on this dataset.

Skewness
Figure 1: Swiss Roll (Source: https://scikit-learn.org/stable/auto_examples/manifold/plot_swissroll.html)

Because there are no good swiss roll datasets available on the Internet directly, we’ll load to tensor created swiss roll dataset with 1000 samples.

swiss_roll =
  Nx.tensor([
    [-8.8313152, 2.10151711, -4.45670876],
    [6.15941887, 5.17977657, 2.58770188],
    [10.23410953, 19.38484837, -6.29460341],
    [11.60978359, 8.25325228, 5.93527204],
    [-9.44716177, 4.1405192, -1.75077878],
    [-9.14066212, 10.03281252, 1.49703653],
    [-8.30319363, 8.17661164, 3.53076713],
    [-3.50163931, 0.06305818, -10.06943069],
    [-5.36417404, 9.28502669, -8.97624018],
    [-5.74223798, 4.48630607, -8.68466132],
    [11.51680254, 1.85733993, -4.09883143],
    [-3.67908164, 6.4411102, -9.98645122],
    [-7.38759241, 6.97403281, -7.00970874],
    [-5.01240594, 5.82777801, 6.84732906],
    [-9.34088572, 10.66496615, 0.6029048],
    [-5.31263585, 13.34134448, 6.66928822],
    [10.78417439, 20.0123519, -5.47919839],
    [7.43646909, 7.77331775, -9.01371917],
    [5.35145344, 18.18259548, 4.48193741],
    [-9.47674306, 1.42425568, -1.09677707],
    [5.57085789, 18.54771524, 4.10142655],
    [-4.80862233, 5.3346213, 6.95886807],
    [11.91401456, 12.42519895, -3.10333003],
    [3.52144312, 4.79076306, -4.1197149],
    [-3.88239859, 1.62842458, 7.37931694],
    [4.50836922, 16.70636732, 5.58104807],
    [12.50699262, 15.08508412, 2.57579946],
    [1.33187579, 11.11716535, 7.56329701],
    [11.94849042, 12.24028964, 5.03235914],
    [-7.62193067, 13.40510227, -6.69624307],
    [4.31595182, 6.04745455, -3.55837632],
    [-0.47401598, 8.12957525, -10.94201811],
    [-7.54759353, 13.36704012, -6.79844625],
    [-2.83238685, 20.62432552, 7.70208861],
    [11.02660149, 9.67867052, -5.06808249],
    [4.97693483, 6.31073777, 12.83620986],
    [12.54070575, 16.70115382, -0.28211401],
    [-3.12322929, 14.36409155, -10.23335682],
    [6.15504322, 6.17994614, 12.20604373],
    [-9.46928984, 7.89309513, -1.38427241],
    [-3.57353186, 20.46941371, 7.49035496],
    [0.74117884, 10.16360345, -11.03776613],
    [5.75830231, 20.12651737, -1.68213898],
    [0.33151929, 19.54850012, -4.77026848],
    [4.06279356, 9.47926784, -3.76096312],
    [4.78869214, 10.34172688, -3.10600293],
    [7.85635468, 6.93968359, 10.99932961],
    [-3.86985637, 2.22281317, -9.89271464],
    [8.19692404, 7.06896747, -8.44132047],
    [0.44250408, 16.90923521, -4.78419875],
    [6.3446155, 16.42643105, 0.53255482],
    [6.07222961, 0.55829229, 2.89848962],
    [4.19249291, 1.48283922, 5.89768184],
    [-5.49908409, 14.64743159, 6.55005453],
    [9.53695925, 13.44975138, -7.15522323],
    [-8.93428834, 14.84191116, 2.14788096],
    [11.02594346, 13.52161869, 7.1507573],
    [1.63692776, 8.98139788, 7.46052236],
    [4.32153517, 12.7298557, 5.77309443],
    [-8.70674945, 15.37617867, 2.72063783],
    [-4.81699699, 10.70378252, 6.95442742],
    [5.86026776, 15.15945121, -1.45905989],
    [6.44342732, 14.61781518, -9.62821188],
    [12.58899959, 5.56269559, 0.34418107],
    [11.89886403, 5.75441231, -3.14647192],
    [10.84038438, 12.56144376, 7.47955699],
    [8.22545033, 12.69229784, 10.68067914],
    [-8.29320994, 7.8364129, 3.5484666],
    [-6.08674638, 4.12945347, 6.12651234],
    [3.74341434, 6.38150565, 13.34880751],
    [4.24853793, 16.95338914, 5.84433787],
    [-9.30843557, 7.95630492, -2.78160162],
    [6.34476788, 13.44014924, 1.44330463],
    [-8.76058105, 17.72028715, 2.59489988],
    [5.63857516, 12.40441207, -10.03157055],
    [-5.14799209, 12.69503064, -9.130977],
    [-4.31509327, 17.38568396, 7.1998396],
    [5.76534121, 20.31141789, -9.97320641],
    [8.51320446, 10.27123949, 10.41535388],
    [4.95945381, 14.00276241, -2.9136638],
    [2.7874212, 8.18363232, 6.93225434],
    [6.82948167, 13.41956201, 11.77423634],
    [1.27886402, 17.65631858, 7.57970442],
    [-8.07758036, 14.30406837, -6.0028668],
    [4.13266509, 16.6570385, -3.70747957],
    [12.5825374, 2.50703498, 0.22986054],
    [-2.2605078, 11.50682434, 7.81518798],
    [3.37348866, 12.04572521, 6.56291498],
    [-6.49904453, 20.73956309, -8.00862441],
    [4.00047908, 18.37510258, -3.80717916],
    [5.98031223, 2.33735624, 3.17611432],
    [6.34227329, 14.14384321, 0.50119354],
    [2.73379039, 3.88664814, 6.96233845],
    [11.79080211, 18.99432667, -3.44035457],
    [12.08528456, 9.28169687, -2.57456403],
    [2.74475645, 4.98017065, -4.48851969],
    [10.80000471, 20.49884326, -5.45345469],
    [-9.28620542, 11.34853999, 0.89233151],
    [-6.77355445, 11.66460162, 5.52425488],
    [2.76730238, 3.66446413, -10.89839044],
    [-5.9174973, 9.29464305, -8.539737],
    [-2.66403786, 10.18609958, 7.73982977],
    [1.8803158, 9.67455061, 13.87565254],
    [4.4742536, 13.94489946, -10.48412406],
    [0.83245284, 15.00524786, -4.81221014],
    [-1.45908722, 18.99011584, 7.90298737],
    [6.34678493, 15.23879447, 0.56368875],
    [6.3059199, 2.99744911, 0.15547907],
    [-9.07517772, 1.61968996, 1.72252085],
    [11.54373672, 11.70252553, -4.03865376],
    [-1.79745436, 17.91955908, -10.67859439],
    [1.98102707, 10.23384359, -4.71087471],
    [-7.38878555, 13.5510619, 4.85862952],
    [1.99277958, 20.74908238, -10.9957415],
    [-9.4754214, 11.41981006, -1.18301902],
    [4.79069647, 11.90037425, 5.26090616],
    [-0.4470774, 4.45873243, 7.89788473],
    [12.60587502, 10.22424953, 1.03455834],
    [-3.02284231, 13.71775046, -10.27395798],
    [1.89692351, 6.52916473, -4.72759871],
    [-8.98162829, 2.45226941, 2.01254378],
    [-8.85074596, 2.16862452, -4.40568126],
    [-9.09477444, 9.10920615, 1.65725701],
    [-1.59420735, 15.92413901, -10.73030283],
    [3.84253976, 19.747862, 6.20639199],
    [2.99588934, 3.7427977, -4.38613248],
    [-7.63287559, 6.76846841, 4.55180338],
    [-9.44495828, 11.30192091, -1.77793528],
    [-9.3714683, 13.50778735, -2.41065506],
    [-5.66214464, 7.21900098, -8.74877148],
    [4.89889258, 1.06334016, 12.87287917],
    [2.48047748, 9.56255577, 7.09672506],
    [2.28405917, 3.0025995, -10.96557981],
    [-4.91976519, 8.21809381, 6.89894202],
    [-6.77264339, 6.50043151, -7.72833737],
    [5.68637128, 17.834621, 3.87542805],
    [-7.36919831, 2.76915445, 4.88207307],
    [-4.67551326, 7.5889942, -9.44150225],
    [4.61082309, 9.74047523, 5.46932658],
    [2.55781647, 17.46513455, -4.55502376],
    [2.54333691, 7.75362726, 7.06453858],
    [-7.93896942, 9.00625301, 4.12306274],
    [4.0461184, 16.86758555, -3.77346553],
    [-6.11865229, 0.83166964, 6.10127456],
    [-1.2958277, 1.05183285, -10.79867562],
    [8.13882818, 10.71772927, -8.48856341],
    [-8.6676732, 18.34670324, 2.80876248],
    [-9.19093659, 10.89141337, 1.30747332],
    [2.83893255, 16.62682712, 13.63964549],
    [8.22365353, 7.59402792, -8.41937623],
    [-9.44834484, 10.16153756, -0.25531781],
    [12.46867557, 5.30573332, 2.85570706],
    [-0.00738733, 18.32033424, -10.99489992],
    [3.77209917, 2.0015116, -10.68876556],
    [-5.77501984, 4.93348532, 6.36060111],
    [4.97557715, 16.12420438, 5.02821176],
    [8.3576441, 12.9549197, -8.30735835],
    [-5.50944353, 20.22917632, 6.54322691],
    [6.2902454, 18.84446588, 12.1239157],
    [-8.82155888, 14.86681432, 2.44575791],
    [3.22446319, 16.79289452, 6.66425592],
    [4.75460865, 0.00877746, -3.14235018],
    [0.91481478, 16.05261378, -4.81403011],
    [11.19712672, 9.66134372, 6.82622795],
    [-9.46768405, 0.83689931, -1.42159092],
    [-5.53375621, 18.3998009, 6.52711765],
    [10.96044847, 6.71630255, -5.18400692],
    [10.4351764, 15.26003256, -6.01297327],
    [4.18087526, 18.69528983, -3.66952153],
    [6.22937585, 19.98937415, -0.2926236],
    [-9.46938658, 2.11172417, -1.38190959],
    [6.35393757, 4.27216985, 0.68868349],
    [6.20282647, 0.38603574, 2.40642951],
    [12.51159145, 10.60661689, 2.53874859],
    [2.2754204, 7.7811052, -4.64043337],
    [10.91956822, 4.13148501, -5.25418863],
    [5.01569359, 15.80616581, -2.84629111],
    [3.78456699, 17.88768735, -3.95705292],
    [5.30830065, 19.72249123, -2.45758728],
    [9.17003027, 16.58250053, -7.54907087],
    [3.67149946, 10.54910499, 6.34340481],
    [-5.68172263, 6.40012611, -8.73322022],
    [2.61491996, 18.1532473, -10.92190052],
    [12.29800693, 7.2092361, -1.76413294],
    [2.50773863, 18.38404008, 13.72935656],
    [2.25900517, 7.69168124, -4.64485463],
    [-8.04833423, 10.64461678, -6.05133859],
    [6.16508487, 0.57625979, -0.56846685],
    [12.29762626, 14.78252085, -1.76581264],
    [-8.79717701, 13.65648542, 2.50630109],
    [7.23127936, 16.81039757, 11.48913947],
    [6.16294153, 2.8500571, 2.57379403],
    [-8.51342001, 16.81909389, -5.19360231],
    [4.64255568, 7.24713667, -3.25744236],
    [12.57202663, 14.81449512, 0.07383412],
    [4.52682027, 3.2278555, 5.56127892],
    [11.85103674, 12.62481635, 5.31396507],
    [5.7433291, 10.23432855, -1.7129558],
    [5.42176832, 2.52761295, -2.28632458],
    [-9.45673506, 0.84492645, -0.37130913],
    [11.28131752, 15.43200474, 6.65806894],
    [11.25562486, 14.54476269, -4.64185679],
    [5.53665318, 20.67696068, -2.09829731],
    [6.24979379, 3.73527961, -0.19059094],
    [6.05762713, 5.84889942, -9.83140315],
    [11.34836526, 7.80851894, 6.51965563],
    [4.62922328, 12.54565264, -3.27070438],
    [3.88597741, 17.65496259, 6.17021748],
    [6.09040706, 12.80852517, -0.83349675],
    [4.98923228, 2.97183159, -2.8782543],
    [4.31831015, 6.77654364, -10.53384521],
    [4.30648895, 20.11727773, 5.78794618],
    [2.59423262, 12.53698395, -4.54270217],
    [3.95395557, 8.62692975, 6.11243484],
    [-0.02429998, 7.4352724, 7.85703681],
    [6.3398709, 1.58844699, 1.50746241],
    [6.01869697, 16.47012319, 3.06507259],
    [0.70415449, 7.7466722, -4.80654807],
    [5.19192276, 4.55229095, 12.73206923],
    [9.18178458, 13.32628919, 9.73366853],
    [6.5502299, 8.93943139, 11.9598403],
    [4.72367491, 9.6064527, -3.17478658],
    [6.34581918, 14.64753812, 0.54955323],
    [9.24500012, 11.79369975, 9.66393968],
    [9.54218705, 18.37170203, 9.32230048],
    [1.75081984, 15.02651711, 7.41840641],
    [12.601052, 3.72181327, 1.3477256],
    [12.51779379, 6.4347312, -0.48887104],
    [4.42082809, 3.39523891, 13.08470694],
    [12.43037807, 13.24812235, -1.09495397],
    [11.09369122, 15.64626259, 7.02494162],
    [-9.41659692, 6.77682741, -2.0676137],
    [12.60580513, 10.18949219, 0.94048968],
    [4.79385999, 1.62751429, 5.25709001],
    [1.42409054, 19.99621531, -4.7940951],
    [-5.9432868, 11.49566492, 6.23700443],
    [9.84608487, 7.61662726, -6.7936431],
    [-2.97012464, 20.87154095, 7.66840673],
    [-3.78808993, 6.20248289, -9.93347304],
    [-8.09109113, 13.5439202, 3.88812014],
    [-1.94526534, 16.40543157, 7.8594572],
    [3.37725903, 6.73427783, -4.20023195],
    [2.18260996, 10.9808, -4.66465822],
    [12.2538423, 14.17331298, -1.95224796],
    [-3.58745667, 14.74504765, 7.48564561],
    [6.2817215, 16.46669624, -0.00915335],
    [4.60124278, 1.52827391, 5.47997853],
    [-4.35618994, 14.37024175, -9.6315042],
    [2.13533057, 15.40890678, 7.26044861],
    [11.66390434, 5.01064442, 5.80382567],
    [6.25953795, 15.03770352, 2.12531083],
    [-6.97076522, 20.55338737, -7.5112793],
    [5.48480022, 3.58901443, 12.5826365],
    [-6.92549248, 12.20969922, -7.56199456],
    [5.44653741, 16.31855163, 4.32387036],
    [12.29441665, 17.75830125, 3.79029361],
    [2.84603717, 2.94229036, 6.89869935],
    [-1.24800989, 3.28858041, 7.9126011],
    [2.56655831, 17.51901644, -4.55209358],
    [-4.23407672, 8.86042395, 7.23563509],
    [-9.42834435, 14.94327951, -0.03421047],
    [-7.24138736, 2.7101173, -7.19317848],
    [-9.19273969, 12.69473007, 1.30035888],
    [-9.25063343, 20.26818152, 1.05783357],
    [3.1527838, 20.68514372, -4.31424557],
    [6.36074527, 17.5196472, 1.04554292],
    [4.3772878, 10.34191952, -3.50546943],
    [12.52915803, 7.23070999, -0.39024239],
    [-3.77133484, 0.87217498, -9.94171654],
    [-6.30584026, 17.99294701, 5.94813829],
    [12.2693674, 8.84908718, 3.89931927],
    [3.86110068, 19.64905301, 13.30585603],
    [12.48585667, 5.97180791, 2.73585372],
    [1.52311473, 15.68329522, 7.50055389],
    [-6.61668276, 6.95179101, -7.89072957],
    [5.45751823, 13.78570209, -2.22950852],
    [5.57564272, 19.69873111, -2.03065558],
    [-9.46772669, 10.53690656, -0.56910505],
    [-9.47114535, 1.9365499, -0.65339504],
    [7.21026985, 0.10135008, 11.50459741],
    [6.36096027, 6.47941012, 1.01172813],
    [-5.25528799, 9.10220351, -9.05521994],
    [1.00409689, 11.59121384, -4.81440925],
    [0.34952479, 12.79532865, -11.02173525],
    [7.07135617, 5.90826433, 11.60525068],
    [9.10414674, 2.12121685, -7.61610888],
    [-9.13399816, 0.25393018, 1.52100015],
    [4.15161677, 12.78203788, -3.69266238],
    [5.10011276, 13.18989975, -2.74104088],
    [-3.61799236, 1.88819289, 7.47522145],
    [-6.47177577, 5.53708564, 5.80480478],
    [-7.96813607, 6.14447986, 4.07925246],
    [-9.46311926, 15.77750804, -0.47685411],
    [10.00346835, 9.53470295, 8.74124915],
    [11.72898907, 6.91332187, -3.5987422],
    [5.9470408, 12.7901538, 12.32825978],
    [12.26320873, 9.46255155, 3.92547593],
    [-9.38822975, 4.48344336, 0.29864154],
    [9.78991479, 3.22969719, -6.86155209],
    [-6.30827905, 1.29334933, 5.94608448],
    [12.361408, 11.64379715, -1.46748043],
    [11.30324182, 7.50511035, 6.61326375],
    [5.99099333, 20.22954069, 3.14584202],
    [2.55340503, 6.36581665, -10.93078332],
    [-8.28459554, 5.99454125, -5.64063984],
    [-0.37540677, 3.32674247, 7.89258732],
    [2.44500437, 16.3876331, 7.11455853],
    [-3.21696928, 16.14180269, -10.19436565],
    [3.10091446, 10.59185756, -4.3387045],
    [-7.81614116, 5.61665964, 4.30163126],
    [0.87011369, 5.12098907, -4.81321782],
    [-1.37994813, 18.6569221, -10.78029786],
    [5.97314654, 1.72113245, 3.19616827],
    [-9.02535826, 5.11330826, -3.90236601],
    [7.95426716, 7.35276076, 10.91705601],
    [-7.92300608, 15.40103177, -6.25234414],
    [-7.81568354, 1.55017873, 4.30227939],
    [-6.52807472, 0.98103109, 5.75447049],
    [5.74224614, 0.10326456, -1.71516719],
    [-6.75182519, 1.59190599, 5.54536644],
    [0.5991863, 4.09046489, 14.08190054],
    [7.52957906, 1.40338925, 11.26278159],
    [-7.9410127, 4.76624703, -6.22410593],
    [0.54610649, 18.93896027, -4.79479657],
    [5.71716963, 6.33811849, 3.81145832],
    [3.47614624, 14.01604482, 6.48991841],
    [7.09570829, 2.58574642, 11.58779908],
    [11.77508873, 20.12065245, 5.52000733],
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    [7.4150793, 7.39107389, 11.35121],
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    [-9.44620147, 7.04982356, -1.76273218],
    [9.38340826, 8.4251251, -7.3244173],
    [2.55860699, 16.24099748, -10.93004566],
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    [-7.62198324, 3.08572018, 4.56610795],
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    [6.3609914, 0.20873186, 1.0007836],
    [8.31257343, 13.25950889, -8.3454169],
    [5.74292616, 13.38404266, -1.71377887],
    [1.85450172, 19.1407703, -11.0073566],
    [3.43440484, 15.38210781, -4.16902115],
    [4.68187389, 17.80879432, -3.21780624],
    [4.37413777, 12.38342191, 5.72047255],
    [8.37687345, 5.71583271, -8.2910022],
    [-8.92912508, 3.51695361, -4.1905712],
    [5.45210322, 2.34019079, -2.23820856],
    [5.14312669, 0.37008062, 12.7561125],
    [-9.42951441, 20.93101766, -0.04570735],
    [-5.33917271, 6.75316158, 6.65273389],
    [5.75121537, 19.01304607, -1.69678142],
    [10.28897652, 12.06908724, -6.2194425],
    [-2.05223603, 15.17399051, 7.84585835],
    [-1.42016368, 2.90483486, -10.77126387],
    [-6.73512703, 9.31084134, -7.76805775],
    [12.43958974, 9.51776908, 3.04242137],
    [11.19924714, 17.51695551, 6.82206591]
  ])

Now we will call MDS.fit/1 on our dataset. To speed up calculations we’ll use EXLA.jit_apply/2 that JITs the computations and make them faster.

key = Nx.Random.key(42)
embedding = EXLA.jit_apply(&MDS.fit(&1, key: &2), [swiss_roll, key])

Extract only embedded data from struct

embedded_data = embedding.embedding

Now we will plot the resulting embedded swiss roll

embedded_data =
  embedded_data
  |> Nx.as_type(:f64)
  |> DF.new()
  |> DF.rename(["x coordinate", "y coordinate"])

Tucan.scatter(embedded_data, "x coordinate", "y coordinate", filled: true)
|> Tucan.set_size(500, 500)
|> Tucan.set_title("Scatterplot showing embedded Swiss roll data set", offset: 20)

As we see, MDS collapsed one dimension and what we see is similar to a cross section of the original dataset.

Digits Dataset

In the next section we change dataset to Digits dataset. It consists of almost 1800 8x8 images with digits.

digits_url =
  "https://github.com/scikit-learn/scikit-learn/raw/main/sklearn/datasets/data/digits.csv.gz"

image_width = 8
image_height = 8

data =
  Req.get!(digits_url).body

df_data = DF.load_csv!(data, delimiter: ",", header: false)
labels = DF.select(df_data, "column_65") |> DF.rename(["labels"])
digits_data = Nx.stack(df_data, axis: 1)

# remove labels from data
digits_data = digits_data[[.., 0..(image_width * image_height - 1)]]
labels

Let’s look how one of the images look like

image = 
  Nx.reshape(digits_data[[1234, ..]], {image_height, image_width})
  |> Nx.as_type({:u, 8})

Tucan.imshow(image, width: 200, height: 200, color_scheme: :greys, reverse: true)
embedding = EXLA.jit_apply(&MDS.fit(&1, key: &2), [digits_data, key])
embedded_data = embedding.embedding

As we can observe, digits with the same label are embedded close to each other. The most problematic label is 5 which is similar to 9 and some samples lie close to each other.

embedded_data =
  embedded_data
  |> Nx.as_type(:f64)
  |> DF.new()
  |> DF.rename(["x coordinate", "y coordinate"])

embedded_data = DF.concat_columns([embedded_data, labels])

Tucan.scatter(embedded_data, "x coordinate", "y coordinate", filled: true, color_by: "labels")
|> Tucan.set_size(500, 500)
|> Tucan.Scale.set_color_scheme(:paired)
|> Tucan.set_title("Scatterplot showing embedded Digits data set", offset: 20)