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46:00 Can we Trust Data-Driven Scientific Discoveries? Can we Trust Data-Driven Scientific Discoveries?	Can we Trust Data-Driven Scientific Discoveries? Genevera Allen discusses "Machine Learning & Scientific Reproducibility: Can we Trust Data-Driven Scientific Discoveries?" As more and more scientific domains are collecting vast… statistics maths machine discovery learning reproducibility clustering discoveries kind techniques cluster science training problem lot groups cancer test dataset harding lots analysis From Belle Taylor on December 18th, 2020 0 likes 7 plays 0 Publisher Centre for Statistics Licence Type All rights reserved Language English Date Created December 8th, 2020
03:39 Topic Overview Topic Overview	Topic Overview Topic Overview iaml neural networks methods method features regression classification linear things bit end networks clustering thing brain analogy algorithm lot quote rug setting kind From Nigel Goddard on September 25th, 2016 1 likes 1,306 plays 0 Licence Type Creative Commons - Attribution
03:25 Divisive clustering (top-down) Divisive clustering (top-down)	Divisive clustering (top-down) Divisive clustering (top-down) iaml hierarchical clustering points cluster means iteration clusters singleton algorithm subset groups property clustering factor instances base depth splits iterations half operation complexity From Nigel Goddard on September 25th, 2016 1 likes 1,827 plays 0 Licence Type Creative Commons - Attribution
00:29 Summary Summary	Summary Summary iaml hierarchical clustering mixture clustering models probabilities algorithm em boundary model techniques canes means ways populations From Nigel Goddard on September 25th, 2016 1 likes 1,228 plays 0 Licence Type Creative Commons - Attribution
07:59 Lance-Williams algorithm Lance-Williams algorithm	Lance-Williams algorithm Lance-Williams algorithm iaml hierarchical clustering distance cluster clusters constants numbers difference j. distances matrix algorithm argument rule minimum decay alright points things max result minus From Nigel Goddard on September 25th, 2016 1 likes 1,809 plays 0 Licence Type Creative Commons - Attribution
08:52 Single-link, complete-link, Ward's method Single-link, complete-link, Ward's method	Single-link, complete-link, Ward's method Single-link, complete-link, Ward's method diameter chain point color yellow cluster individual connect measure caption complete clustering circles single linkage merge length smallest connecting distance metric deviation iaml internet protocols complete closest means merge red hierarchical clustering optical spectrum effects libertarian theory merging blue individualism distance algorithm average pretend iteration euclidean political philosophy euclidean geometry points clusters pairs pair deviations chains linkage centroid radius c2 c1 metric result From Nigel Goddard on September 25th, 2016 1 likes 2,100 plays 0 Licence Type Creative Commons - Attribution
05:03 Agglomerative clustering - dendrogram Agglomerative clustering - dendrogram	Agglomerative clustering - dendrogram Agglomerative clustering - dendrogram iaml hierarchical clustering distance clusters cluster points clustering threshold point dendrogram arc tree things space dataset decrease distances elbow drops function merge plot From Nigel Goddard on September 25th, 2016 1 likes 1,717 plays 0 Licence Type Creative Commons - Attribution
03:03 Agglomerative clustering (bottom-up) Agglomerative clustering (bottom-up)	Agglomerative clustering (bottom-up) Agglomerative clustering (bottom-up) iaml hierarchical clustering clusters distance cluster metric points algorithm iteration elements ci individual collection matrix operations implementation tree cj singleton point clustering idea From Nigel Goddard on September 25th, 2016 0 likes 1,747 plays 0 Licence Type Creative Commons - Attribution
04:06 Flat vs hierachical clustering Flat vs hierachical clustering	Flat vs hierachical clustering Flat vs hierachical clustering iaml hierarchical clustering clusters cluster hierarchy groupings level strategy bottom question pairs tree individuals subgroups individual subclusters point points bit algorithm means partition From Nigel Goddard on September 25th, 2016 1 likes 1,820 plays 0 Licence Type Creative Commons - Attribution
02:32 Introduction to mixture models Introduction to mixture models	Introduction to mixture models Introduction to mixture models iaml mixture-models clusters clustering cluster means probability methods parameters space distribution models mixture variances gaussian kind points ways dataset auto algorithm em From Nigel Goddard on September 25th, 2016 0 likes 2,320 plays 0 Licence Type Creative Commons - Attribution
01:45 Summary Summary	Summary Summary iaml k-means distance cluster variance clustering means configuration point centroids initializations representation image yellow red clusters points property media manhattan centroid notion From Nigel Goddard on September 25th, 2016 0 likes 1,331 plays 0 Licence Type Creative Commons - Attribution
02:24 Paired evaluation and Rand index Paired evaluation and Rand index	Paired evaluation and Rand index Paired evaluation and Rand index iaml k-means pairs clusters humans pair classes algorithm evaluation slide strategy cd dataset instances clustering reference bit effort alignment pairing advantage lecture From Nigel Goddard on September 25th, 2016 1 likes 1,788 plays 0 Licence Type Creative Commons - Attribution
12:50 Intrinsic evaluation and alignment Intrinsic evaluation and alignment	Intrinsic evaluation and alignment Intrinsic evaluation and alignment iaml k-means clusters cluster class reference accuracy clustering overlap alignment assignments positives evaluation c1 row points answer classes strategy problem c2 elements From Nigel Goddard on September 25th, 2016 1 likes 1,996 plays 0 Licence Type Creative Commons - Attribution
06:39 Evaluating clustering systems Evaluating clustering systems	Evaluating clustering systems Evaluating clustering systems iaml k-means clustering task cluster clusters classification images algorithm pairs classifier evaluation classes bit groups question centroids variance distance judgments bunch bitmaps From Nigel Goddard on September 25th, 2016 1 likes 1,945 plays 0 Licence Type Creative Commons - Attribution
05:38 K-means objective function K-means objective function	K-means objective function K-means objective function iaml k-means points cluster distance centroid means centroids point clustering initializations configuration variance minimum procedure property lots properties algorithms infrastructure computing dataset From Nigel Goddard on September 25th, 2016 1 likes 1,842 plays 0 Licence Type Creative Commons - Attribution

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