排名子树 修剪和重新植入

Lena Collienne1, Chris Whidden2, Alex Gavryushkin3,4

  • 1Biological Data Science Laboratory, School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand. lena@lenacoll.de.

PubMed
概括

我们介绍了新的排名子树修剪和重新植入 (SPR) 树空间,用于分析遗传学时间树. 令人惊的是,添加叶子可以减少排名SPR距离,影响进化推理算法.

相关概念视频

Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
86
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.6K
Sieve Analysis and Grading Curves01:19

Sieve Analysis and Grading Curves

Sieve analysis is a method used to determine the particle size distribution of aggregate materials. This process involves the following steps:
364
Types of Aggregate Grading01:15

Types of Aggregate Grading

Aggregate grading is crucial in economically obtaining a concrete mix with adequate strength, reasonable workability, and minimal segregation. There are four types of aggregate gradation: well-graded, uniformly (or one-sized) graded, gap-graded, and open-graded.
Well-graded aggregates include a complete range of necessary size fractions that fit together to create a dense matrix with minimal voids, represented by a smooth, continuous gradation curve. This type of grading ensures good...
511
Pedigree Analysis01:35

Pedigree Analysis

Overview
84.3K
Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
236