# Questions tagged [partitioning]

A partition is an assignment of every element of a set into 1 & only 1 subset w/ no empty subsets. A common instance of partitioning in statistics is the partitioning of sums of squares for F-tests.

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### In this concrete example of applying sklearn knn (with kd_tree) on Iris Data Set, how many partitions are there?

The k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression. In both cases, the input consists of the k closest training examples in the ...
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### Recursive partitioning tree vs neural network model

I hope this question helps shed some light on trees vs neural models. I recently came across a model tree, or a recursive partitioning model. It is basically a decision tree that has linear regression ...
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### Does the multinomial coefficient create combinations or permutations?

I am looking at this formula I just want to make sure I get it. For example, if I want to split a fifty-two card deck into all the possible combinations of four, thirteen card hands, then I get: 52!...
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### Random partition techniques for lasso and elastic net

I think this is the correct place for this question. I have implemented lasso, elastic net and a different estimator on a real data set. I used 10-fold cross-validation (CV) one time without ...
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### default plot for mob object (glm tree) not returned; using party package [closed]

I'm trying to plot a glm tree using the package party. Per the reference guide, the default plot of the terminal node should be a spinogram as in this image but I ...
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### Optimization program

I am trying to merge (and sum) $m$ time series into 2 groups. My goal is to minimize the standard deviation of the difference between the 2 groups. In other word, there can be an offset between the 2 ...
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### Statistical test of fairness of partitioning

I have a question about a statistical test, but I lack the proper terminology so I'll try to explain in my own words. Say I have a collection of $N$ objects. The collection is partitioned into $p$ ...
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### Variation partition analysis: morphology-climate correlation, controlling for geography

I'm working with three datasets with informations about individuals: morphological data, climatic data of the individual sampling site and geographical data. My objective is to assess whether ...
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### Cluster/partition by time

I have a dataset of different events in time. I want to group/cluster/partition the data by datetime. A small example of the time of the data might be: [19-09-2018 12:00, 19-09-2018 12:01, 19-09-2018 ...
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### Estimation of partitioning error in next-generation sequencing experiments

[Edited: explanation of the partitioning error] I would like to estimate how the initial number of molecules (or the level of gene expression) affects reproducibility between technical replicates of ...
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### Adjusted Rand Index with different size inputs

Forgive me if my terminology is off, this concept is somewhat new to me. I'm trying to run an ARI calculation between two partitions which contain a different number of clusters, where each cluster ...
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### Appropriate partition region in a decision tree?

I have the following partition region for a decision tree, but I do not think it is a valid region: $R=(\vec{X}=(X_1, X_2, ..., X_p)^T\in \mathbb{R}^p: X_1X_2 \geq 3)$ I feel that this is not a ...
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### Predictors in random Forest

I am building a random forest to predict a binary variable y. I have several predictors named x1..n. One predictor, lets say x1, is a very strong predictor of y but only in some cases (see below) ...
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### Estimates for k-d tree partition cells and for Voronoi partition cells

Let us have a $k$-d tree in a unit cube in ${\mathbb R}^k$. Let the points of the tree in the cube be i.i.d. with some density bounded away from 0. How can I estimate the volumes of partition ...
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### How to partition set of items into subsets with similar mean, variance and number of elements - looking for some help

Short version: Given I have a list of 120 traits (happy, sad, etc.) evaluated on a number of scales ranging from -5 (for example highly negative) to +5 (for example highly positive), how can I group ...
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### Possible explanations for Imputation before train-test split?

I'm working on a real world data set containing missing information. I understand imputing missing values before data partitioning can lead to leakage of information. I'm using this R package MissMech ...
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### Clustering restaurant dishes

I have data about restaurants, their dishes and customer's orders. Then I want to cluster dishes in restaurant's menu by customer order. So clusters will be dishes in order and criteria of similarity ...
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### Cluster non-vector data based on similarity rating

I have a list $S$ of $N$ non-vector elements (in this case words or concepts), and I'd like to partition them into k subsets of similar words. For each pair $(a,b)$ with $a,b \in S$, I have a number ...
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### Cluster real numbers

I have a set of precise measurements, and what I want to do is count the frequency (how many time it appears) for each value. The problem is that these are very precise measurements and with a naive ...
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### How to choose the relative sizes of training and validation sets?

When I work with the methods of data mining, the data is split in training and validations data samples (and sometimes test). I know training + validation = 100%. Which criteria can I use to find a ...
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### How to build a decision tree with a constraint on sensitivity?

I am trying to develop a classification model on a sample of people which will discriminate between "Type A" and "Not-Type A" people. Due to external factors, the minimum sensitivity for this ...
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### Least Squared Regressions on Partitioned Data

Say I have 800 (X,Y) data points, and I do a LSQ fit and get y = mx+b Then I think to myself, of the 800 data points, 500 are males and 300 are females, so I ...
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### What are the differences between Lloyd's, MacQueen's and Hartigan's algorithms for K-Means?

There are three distinct algorithms for the K-Means function in R. These are: Lloyd's MacQueen's Hartigan's I believe I understand how Lloyd's works. 1. The cluster centers are chosen. 2. Points are ...
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### What approaches use multiple eigenvectors in graph spectral clustering?

Background: In Newman's PNAS 2006 paper Modularity and community structure in networks, the first eigenvector splits the graph in two clusters, and then each cluster can be further divided by ...
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### Is K-Medoids really better at dealing with outliers than K-Means? (with example showing the contrary)

K-Medoids and K-Means are two popular methods of partitional clustering. The consensus is that K-Medoids is better at clustering data when there are outliers (source). This is because it chooses data ...
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### Efficient ways to partition rows of augmented design matrix $[X|y]$ into subsets with similar regression results?

Imagine I have $n$ observations on a regression model; are there any reasonably efficient methods for partitioning that into two (or more) roughly equally sized groups which almost reproduce the ...
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### Catalan numbers and gambler's ruin paths

Edit I've edited this question several times, and in the end I essentially answered my own question. No need to answer it yourself. I made it slightly less long and rambling, in case anyone else is ...