Components of Random Forests

1992 ◽  
Vol 1 (1) ◽  
pp. 35-52 ◽  
Author(s):  
Tomasz Łuczak ◽  
Boris Pittel
Keyword(s):  
Phase Transition ◽  
Random Forest ◽  
Asymptotic Behaviour ◽  
Random Graph ◽  
Random Forests ◽  
Limit Distribution ◽  
The Family ◽  
Supercritical Phase

A forest ℱ(n, M) chosen uniformly from the family of all labelled unrooted forests with n vertices and M edges is studied. We show that, like the Érdős-Rényi random graph G(n, M), the random forest exhibits three modes of asymptotic behaviour: subcritical, nearcritical and supercritical, with the phase transition at the point M = n/2. For each of the phases, we determine the limit distribution of the size of the k-th largest component of ℱ(n, M). The similarity to the random graph is far from being complete. For instance, in the supercritical phase, the giant tree in ℱ(n, M) grows roughly two times slower than the largest component of G(n, M) and the second largest tree in ℱ(n, M) is of the order n⅔ for every M = n/2 +s, provided that s3n−2 → ∞ and s = o(n), while its counterpart in G(n, M) is of the order n2s−2 log(s3n−2) ≪ n⅔.

scholarly journals An Application of an Embedded Model Estimator to a Synthetic Nonstationary Reservoir Model With Multiple Secondary Variables

2021 ◽  
Vol 4 ◽  
Author(s):  
Colin Daly
Keyword(s):  
Random Forest ◽  
Random Forests ◽  
Target Location ◽  
Three Dimensional ◽  
Stochastic Simulations ◽  
Interpolation Algorithm ◽  
Reservoir Model ◽  
The Family ◽  
Embedded Model ◽  
Consistency Properties

A method (Ember) for nonstationary spatial modeling with multiple secondary variables by combining Geostatistics with Random Forests is applied to a three-dimensional Reservoir Model. It extends the Random Forest method to an interpolation algorithm retaining similar consistency properties to both Geostatistical algorithms and Random Forests. It allows embedding of simpler interpolation algorithms into the process, combining them through the Random Forest training process. The algorithm estimates a conditional distribution at each target location. The family of such distributions is called the model envelope. An algorithm to produce stochastic simulations from the envelope is demonstrated. This algorithm allows the influence of the secondary variables, as well as the variability of the result to vary by location in the simulation.

scholarly journals Species-specific audio detection: A comparison of three template-based classification algorithms using random forests

2017 ◽  
Author(s):  
Carlos J Corrada Bravo ◽  
Rafael Álvarez Berríos ◽  
T. Mitchell Aide
Keyword(s):  
Random Forest ◽  
Random Forests ◽  
Random Forest Classifier ◽  
Classification Algorithms ◽  
Statistical Features ◽  
Web Based ◽  
Average Accuracy ◽  
Species Specific ◽  
Web Based System

We developed a web-based cloud-hosted system that allow users to archive, listen, visualize, and annotate recordings. The system also provides tools to convert these annotations into datasets that can be used to train a computer to detect the presence or absence of a species. The algorithm used by the system was selected after comparing the accuracy and efficiency of three variants of a template-based classification. The algorithm computes a similarity vector by comparing a template of a species call with time increments across the spectrogram. Statistical features are extracted from this vector and used as input for a Random Forest classifier that predicts presence or absence of the species in the recording. The fastest algorithm variant had the highest average accuracy and specificity; therefore, it was implemented in the ARBIMON web-based system.

Ballots, queues and random graphs

1989 ◽  
Vol 26 (1) ◽  
pp. 103-112 ◽  
Author(s):  
Lajos Takács
Keyword(s):  
Real Number ◽  
Random Graph ◽  
Random Graphs ◽  
Limit Distribution ◽  
Positive Real Number ◽  
Positive Real ◽  
Ballot Theorem

This paper demonstrates how a simple ballot theorem leads, through the interjection of a queuing process, to the solution of a problem in the theory of random graphs connected with a study of polymers in chemistry. Let Γn(p) denote a random graph with n vertices in which any two vertices, independently of the others, are connected by an edge with probability p where 0 < p < 1. Denote by ρ n(s) the number of vertices in the union of all those components of Γn(p) which contain at least one vertex of a given set of s vertices. This paper is concerned with the determination of the distribution of ρ n(s) and the limit distribution of ρ n(s) as n → ∞and ρ → 0 in such a way that np → a where a is a positive real number.

For Honor, for Toxicity

2021 ◽  
Vol 5 (CHI PLAY) ◽  
pp. 1-29
Author(s):  
Alessandro Canossa ◽  
Dmitry Salimov ◽  
Ahmad Azadvar ◽  
Casper Harteveld ◽  
Georgios Yannakakis
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Random Forests ◽  
Initial Study ◽  
Unfair Advantage ◽  
Offensive Behavior ◽  
Forest Models ◽  
Random Forest Models ◽  
Action Type ◽  
Degree Of Severity

Is it possible to detect toxicity in games just by observing in-game behavior? If so, what are the behavioral factors that will help machine learning to discover the unknown relationship between gameplay and toxic behavior? In this initial study, we examine whether it is possible to predict toxicity in the MOBA gameFor Honor by observing in-game behavior for players that have been labeled as toxic (i.e. players that have been sanctioned by Ubisoft community managers). We test our hypothesis of detecting toxicity through gameplay with a dataset of almost 1,800 sanctioned players, and comparing these sanctioned players with unsanctioned players. Sanctioned players are defined by their toxic action type (offensive behavior vs. unfair advantage) and degree of severity (warned vs. banned). Our findings, based on supervised learning with random forests, suggest that it is not only possible to behaviorally distinguish sanctioned from unsanctioned players based on selected features of gameplay; it is also possible to predict both the sanction severity (warned vs. banned) and the sanction type (offensive behavior vs. unfair advantage). In particular, all random forest models predict toxicity, its severity, and type, with an accuracy of at least 82%, on average, on unseen players. This research shows that observing in-game behavior can support the work of community managers in moderating and possibly containing the burden of toxic behavior.

Ballots, queues and random graphs

1989 ◽  
Vol 26 (01) ◽  
pp. 103-112 ◽  
Author(s):  
Lajos Takács
Keyword(s):  
Real Number ◽  
Random Graph ◽  
Random Graphs ◽  
Limit Distribution ◽  
Positive Real Number ◽  
Positive Real ◽  
Ballot Theorem

This paper demonstrates how a simple ballot theorem leads, through the interjection of a queuing process, to the solution of a problem in the theory of random graphs connected with a study of polymers in chemistry. Let Γ n (p) denote a random graph with n vertices in which any two vertices, independently of the others, are connected by an edge with probability p where 0 &lt; p &lt; 1. Denote by ρ n (s) the number of vertices in the union of all those components of Γ n (p) which contain at least one vertex of a given set of s vertices. This paper is concerned with the determination of the distribution of ρ n (s) and the limit distribution of ρ n (s) as n → ∞and ρ → 0 in such a way that np → a where a is a positive real number.

scholarly journals Contagions in random networks with overlapping communities

2015 ◽  
Vol 47 (4) ◽  
pp. 973-988 ◽  
Author(s):  
Emilie Coupechoux ◽  
Marc Lelarge
Keyword(s):  
Phase Transition ◽  
Random Graph ◽  
Epidemic Model ◽  
Branching Process ◽  
Branching Processes ◽  
Graph Model ◽  
Single Individual ◽  
Overlapping Communities ◽  
Random Graph Model ◽  
The Mean

We consider a threshold epidemic model on a clustered random graph model obtained from local transformations in an alternating branching process that approximates a bipartite graph. In other words, our epidemic model is such that an individual becomes infected as soon as the proportion of his/her infected neighbors exceeds the threshold q of the epidemic. In our random graph model, each individual can belong to several communities. The distributions for the community sizes and the number of communities an individual belongs to are arbitrary. We consider the case where the epidemic starts from a single individual, and we prove a phase transition (when the parameter q of the model varies) for the appearance of a cascade, i.e. when the epidemic can be propagated to an infinite part of the population. More precisely, we show that our epidemic is entirely described by a multi-type (and alternating) branching process, and then we apply Sevastyanov's theorem about the phase transition of multi-type Galton-Watson branching processes. In addition, we compute the entries of the mean progeny matrix corresponding to the epidemic. The phase transition for the contagion is given in terms of the largest eigenvalue of this matrix.

ON THE STRUCTURE OF SUPERCRITICAL PHASE TRANSITION

1990 ◽  
Vol 05 (14) ◽  
pp. 1081-1087 ◽  
Author(s):  
YUMI S. HIRATA ◽  
HISAKAZU MINAKATA
Keyword(s):  
Phase Transition ◽  
Statistical Mechanics ◽  
Order Phase Transition ◽  
False Vacuum ◽  
Close Analogy ◽  
First Order ◽  
First Order Phase Transition ◽  
Supercritical Phase ◽  
First Order Phase ◽  
Irreversible Nature

A novel physical picture is presented for the normal-to-supercritical "phase" transition in QED around a large-Z nucleus. The process is described as the decay of the false vacuum in close analogy to the first-order phase transition in statistical mechanics. The irreversible nature of the transition is pointed out and the physical implications of this picture are discussed.

Finite-dimensional coagulation-fragmentation dynamics

2018 ◽  
Vol 28 (05) ◽  
pp. 851-868
Author(s):  
Jack Carr ◽  
Matab Alghamdi ◽  
Dugald B. Duncan
Keyword(s):  
Phase Transition ◽  
Asymptotic Behaviour ◽  
Numerical Approximation ◽  
Finite System ◽  
Numerical Results ◽  
Centre Manifold ◽  
Finite Dimensional ◽  
Time Period ◽  
Fragmentation Dynamics ◽  
Loss Of Mass

We examine a finite-dimensional truncation of the discrete coagulation-fragmentation equations that is designed to allow mass to escape from the system into clusters larger than those in the truncated problem. The aim is to model within a finite system the process of gelation, which is a type of phase transition observed in aerosols, colloids, etc. The main result is a centre manifold calculation that gives the asymptotic behaviour of the truncated model as time [Formula: see text]. Detailed numerical results show that truncated system solutions are often very close to this centre manifold, and the range of validity of the truncated system as a model of the full infinite problem is explored for systems with and without gelation. The latter cases are mass conserving, and we provide an estimate using quantities from the centre manifold calculations of the time period and the truncated system can be used for before loss of mass which is apparent. We also include some observations on how numerical approximation can be made more reliable and efficient.

Phase transition in the family LaxBi4−xTi3O12: In relation to lattice symmetry and distortion

1980 ◽  
Vol 35 (3) ◽  
pp. 402-406 ◽  
Author(s):  
Masaji Shimazu ◽  
Junzo Tanaka ◽  
Kunitaka Muramatsu ◽  
Masayuki Tsukioka
Keyword(s):  
Phase Transition ◽  
Lattice Symmetry ◽  
The Family
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