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  2. Task 7: Training the HMM Your aim is to ...

    https://www.cl.cam.ac.uk/teaching/1819/MLRD/tasks/task7.pdf
    9 Jan 2019: In the thirdsession, you will use the same approach (and much the same code) to predictproperties of real biological sequence data. ... 1. Download and examine the dice dataset. This dataset contains a numberof files corresponding to sequences of states.
  3. 5: Overtraining and Cross-validation - Machine Learning and…

    https://www.cl.cam.ac.uk/teaching/1920/L90/MLRD_1819_slides5_overtraining_cv.pdf
    9 Oct 2019: 5: Overtraining and Cross-validationMachine Learning and Real-world Data. Paula Buttery(based on slides created by Simone Teufel). ... Calculate variance between splits. Second task today. Use the precious test data for the first time (on the bestsystem
  4. Task 9: Biological applications. Data This practical explores the ...

    https://www.cl.cam.ac.uk/teaching/1819/MLRD/tasks/task9.pdf
    16 Feb 2019: Task 9: Biological applications. Data. This practical explores the application of Hidden Markov models to biologicaldata. ... If you think about this task, you will realize that our first-order HMM cannotcompletely capture the structure of the data.
  5. 5: Overtraining and Cross-validation - Machine Learning and…

    https://www.cl.cam.ac.uk/teaching/1819/MLRD/slides/slides5.pdf
    1 Feb 2019: 5: Overtraining and Cross-validationMachine Learning and Real-world Data. Paula Buttery(based on slides created by Simone Teufel). ... Calculate variance between splits. Second task today. Use the precious test data for the first time (on the bestsystem
  6. IA Scientific Computing 2019 / 2020Damon Wischik, Computer Science,…

    https://www.cl.cam.ac.uk/teaching/1920/SciComp/scicomp.pdf
    28 Nov 2019: 3 Working with data 193.1 Preamble. 193.2 What data looks like. ... We’ll lookat the two standard ways of arranging data, data frames and indexed arrays.
  7. TC10-simplified

    www.phase-trans.msm.cam.ac.uk/map/data/tar/TC10data.xls
    30 Dec 2019: TC10-simplified. C. Mn. Ni. Mo. V. Cr. Cu. Al. Nb. Si. W. Ti. Co. P. S. TC. K. Label. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 20. 73.3. Pure_01. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 27. 80.2. Pure_02. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
  8. 6: Uncertainty and Human Agreement - Machine Learning and Real-world…

    https://www.cl.cam.ac.uk/teaching/1819/MLRD/slides/slides6.pdf
    4 Feb 2019: 6: Uncertainty and Human AgreementMachine Learning and Real-world Data (MLRD). Paula Buttery(based on slides created by Simone Teufel). ... Many movie reviews are neither positive nor negative. So far, your data sets have contained only the clearly
  9. Case Splitting in an Automatic Theorem Proverfor Real-Valued Special…

    https://www.cl.cam.ac.uk/~lp15/papers/Arith/case-splitting.pdf
    8 Aug 2019: The depth-first searchis managed by a data structure called the split stack. ... The waiting set is implemented as apriority queue using a purely functional data structure.
  10. Annual Report 2007.indd

    https://www.arch.cam.ac.uk/files/miar-report-2007.pdf
    22 Aug 2019: The Workshop also featured tutorial sessions on various aspect of archaeogenetics as a discipline, including discussions on understanding of archaeozoological data, sample selection, taphonomy etc. ... to key skills in the statistical manipulation of
  11. Annual Report 2007.indd

    https://www.arch.cam.ac.uk/files/miar-report-2007.pdf
    22 Aug 2019: The Workshop also featured tutorial sessions on various aspect of archaeogenetics as a discipline, including discussions on understanding of archaeozoological data, sample selection, taphonomy etc. ... to key skills in the statistical manipulation of

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