Table_1_Clinical Functional Seizure Score (CFSS): a simple algorithm for clinicians to suspect functional seizures.DOCX by Mohammad Dashtkoohi (15417886)

Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty by Arnaud Liehrmann (10970682)

“…This penalty was proposed by Verzelen et al. and achieves optimal rates for changepoint detection and changepoint localization in a non-asymptotic scenario. Our proposed algorithm, Multiscale Functional Pruning Optimal Partitioning (Ms.FPOP), extends functional pruning ideas presented in Rigaill and Maidstone et al. to multiscale penalties. …”

Flowchart of one iteration of the CE-Symm algorithm. by Spencer E. Bliven (6672755)

One iteration of the NSGA-II algorithm. by Erick Axel Padilla-García (16839233)

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Mapping indices: WheresWalker SNP index, Het^wt, and homozygosity values for zebrafish and maize datasets. by McKenna Feltes (11242085)

Subjects:

Comparison of compression rates of DDQR and Geco3 using simulated data around the region where the performance of DDQR exceeds that of GeCo3. by Yujun Wang (1947196)

Summary of results of naïve Bayes algorithms. by Christopher E. Niemczak (8586861)

“…Algorithms trained without auditory variables as features were statistically worse (p < .001) in both the primary measure of area under the curve (0.82/0.78) and the secondary measure of accuracy (72.3%/74.5%) for the Gaussian and kernel algorithms respectively.…”

Constructing the dynamical law. by Robert Marsland (8616483)

Definitions of global parameters used for constructing random ecosystems. by Robert Marsland (8616483)

Performance of the three algorithms. by Juanjuan Lin (2096830)

“…An integrated framework based on a novel genetic algorithm and the Frank—Wolfe algorithm is designed to solve the stochastic model. …”

The GOR4 and SOPMA algorithm findings. by Ahmad Abdullah Mahdeen (19704401)

Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

“…These implementations need to utilize high-precision arithmetic, and are programmed in the Python programming language. A thorough comparison with existing R functions allows the identification of cases when the latter fail, and provide further guidance to their use.…”

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Subjects:

Brief sketch of the quasi-attraction/alignment algorithm. by Takayuki Niizato (162226)

“…The focal agent selects its next direction randomly based on . (D) A brief sketch of the avoidance algorithm. Upper: Each direction is extended to the repulsion area = {<b><i>r</i></b>||<b><i>r</i></b>| = <i>R</i>}, where is the minimal sphere cap that covers all points on . …”

Left: the algorithm’s best estimate of where to put breakpoints for each number of breakpoints considered. by Zhengtian Li (5076704)

Comparison of algorithms in two cases. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Flow of the NSGA-II algorithm. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Simulation results by genetic algorithms (GAs). by Yuji Omachi (15307241)

Algorithms for Sparse Support Vector Machines by Alfonso Landeros (798926)

“…Penalties still appear, but serve a different purpose. The proximal distance principle takes a loss function <math><mrow><mi>L</mi><mo>(</mo><mi>β</mi><mo>)</mo></mrow></math> and adds the penalty <math><mrow><mi>ρ</mi><mn>2</mn>dist<mrow><mrow><mo>(</mo><mi>β</mi><mo>,</mo><msub><mrow><mi>S</mi></mrow><mi>k</mi></msub><mo>)</mo></mrow></mrow><mn>2</mn></mrow></math> capturing the squared Euclidean distance of the parameter vector <math><mi>β</mi></math> to the sparsity set <i>S_k</i> where at most <i>k</i> components of <math><mi>β</mi></math> are nonzero. …”