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Probabilistic classification algorithm
Despite the use of Bayes' theorem in the classifier's decision rule, naive Bayes is not (necessarily) a Bayesian method, and naive Bayes models can be fit
Naive_Bayes_classifier
Classification algorithm in statistics
In statistical classification, the Bayes classifier is the classifier having the smallest probability of misclassification of all classes using the same
Bayes_classifier
Statistics and machine learning technique
number of independent component classifiers as class labels gives the highest accuracy. The Bayes optimal classifier is a classification technique. It
Ensemble_learning
Statistical classification in machine learning
simpler definition is to say that a linear classifier is one whose decision boundaries are linear. Such classifiers work well for practical problems such as
Linear_classifier
targets Laplace–Bayes estimator – Formula in probability theoryPages displaying short descriptions of redirect targets Naive Bayes classifier – Probabilistic
List of things named after Thomas Bayes
List_of_things_named_after_Thomas_Bayes
Error rate in statistical mathematics
measurable}}}R(h)} A hypothesis h with R(h) = R* is called a Bayes hypothesis or Bayes classifier. In terms of machine learning and pattern classification
Bayes_error_rate
Categorization of data using statistics
classification, especially in a concrete implementation, is known as a classifier. The term "classifier" sometimes also refers to the mathematical function, implemented
Statistical_classification
problem of the popular naive Bayes classifier. It frequently develops substantially more accurate classifiers than naive Bayes at the cost of a modest increase
Averaged one-dependence estimators
Averaged_one-dependence_estimators
population is assigned to the class it really belongs to. The bayes classifier is the classifier which assigns classes optimally based on the known attributes
Classification_rule
Tasks in machine learning
artificial neural networks) of the model. The model (e.g. a naive Bayes classifier) is trained on the training data set using a supervised learning method
Training, validation, and test data sets
Training,_validation,_and_test_data_sets
Topics referred to by the same term
science and statistics, Bayesian classifier may refer to: any classifier based on Bayesian probability a Bayes classifier, one that always chooses the class
Bayesian_classifier
Overview of and topical guide to machine learning
regression (LARS) Classifiers Probabilistic classifier Naive Bayes classifier Binary classifier Linear classifier Hierarchical classifier Dimensionality
Outline_of_machine_learning
Regression for more than two discrete outcomes
statistically independent from each other (unlike, for example, in a naive Bayes classifier); however, collinearity is assumed to be relatively low, as it becomes
Multinomial logistic regression
Multinomial_logistic_regression
Machine learning paradigm
decision graphs, etc.) Multilinear subspace learning Naive Bayes classifier Maximum entropy classifier Conditional random field Nearest neighbor algorithm Probably
Supervised_learning
Model for generating observable data in probability and statistics
estimated probability distributions, plus Bayes rule. This type of classifier is called a generative classifier, because we can view the distribution P
Generative_model
Non-parametric classification method
method. The most intuitive nearest neighbour type classifier is the one nearest neighbour classifier that assigns a point x to the class of its closest
K-nearest_neighbors_algorithm
Machine learning calibration technique
of classification models, including boosted models and even naive Bayes classifiers, which produce distorted probability distributions. It is particularly
Platt_scaling
Sending data between network nodes when an event of interest is triggered at a sensor
node. Below are a few examples of algorithms that solve the optimal Bayes classifier. They all require a set of training vectors to simulate or re-enact
Event_detection_for_WSN
Computer vision library
Expectation-maximization algorithm k-nearest neighbor algorithm Naive Bayes classifier Artificial neural networks Random forest Support vector machine (SVM)
OpenCV
Method of statistical inference
Bayesian inference (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is a method of statistical inference in which Bayes' theorem is used to calculate a probability
Bayesian_inference
Concept in statistics
the class-conditional marginal densities of data when using a naive Bayes classifier, which can improve its prediction accuracy. Let x = ( x 1 , x 2 , x
Kernel_density_estimation
Probabilistic graphical representation of causal relationships
A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a
Bayesian_network
team of volunteers. It uses a naive Bayes classifier to filter mail. This allows the filter to "learn" and classify mail according to the user's preferences
POPFile
Electronic sensor for odor detection
S2CID 237149759. Dutta, Ritaban; Dutta, Ritabrata (2006). "Intelligent Bayes Classifier (IBC) for ENT infection classification in hospital environment". BioMedical
Electronic_nose
Bayesian statistical inference method
integrated out. Empirical Bayes methods can be seen as an approximation to a fully Bayesian treatment of a hierarchical Bayes model. In, for example, a
Empirical_Bayes_method
chain Monte Carlo (MCMC) Minimum redundancy feature selection Naive Bayes classifier Non-negative matrix factorization OPTICS Prefrontal cortex basal ganglia
List of artificial intelligence algorithms
List_of_artificial_intelligence_algorithms
Process of categorizing documents
Multiple-instance learning Naive Bayes classifier Natural language processing approaches Rough set-based classifier Soft set-based classifier Support vector machines
Document_classification
Ensemble learning method
learner is defined as a classifier that performs only slightly better than random guessing, whereas a strong learner is a classifier that is highly correlated
Boosting_(machine_learning)
Image classification model
computer vision. Simple Naive Bayes model and hierarchical Bayesian models are discussed. The simplest one is Naive Bayes classifier. Using the language of graphical
Bag-of-words model in computer vision
Bag-of-words_model_in_computer_vision
Statistical technique for smoothing categorical data
Linguistics. Pseudocounts Bayesian interpretation of pseudocount regularizers A video explaining the use of Additive smoothing in a Naïve Bayes classifier
Additive_smoothing
Intelligence of machines
Bayes classifier is reportedly the "most widely used learner" at Google, due in part to its scalability. Neural networks are also used as classifiers
Artificial_intelligence
Topics referred to by the same term
Australian steam locomotives Boeing NB, a 1923 training aircraft Naive Bayes classifier, in statistics Neuroblastoma, a type of cancer Nominal bore or nominal
NB
Principle in statistical learning theory
min} }}\,{R(h)}.} For classification problems, the Bayes classifier is defined to be the classifier minimizing the risk defined with the 0–1 loss function
Empirical_risk_minimization
classification of image data is based on the Bayes minimum error classifier (also known as a naive Bayes classifier). Present the pixel: A pixel is denoted
Contextual image classification
Contextual_image_classification
Assumptions for inference in machine learning
maximize conditional independence. This is the bias used in the Naive Bayes classifier. Minimum cross-validation error: when trying to choose among hypotheses
Inductive_bias
Probabilistic model
Bayesian networks. One of the simplest Bayesian Networks is the Naive Bayes classifier. The next figure depicts a graphical model with a cycle. This may be
Graphical_model
Data representation for machine learning
For example, suppose the final goal is to classify images with highly redundant pixels. A naive Bayes classifier will assume the pixels are statistically
Factorial_code
Processing of email to organize it according to specified criteria
use statistical document classification techniques such as the naive Bayes classifier while others use natural language processing to organize incoming emails
Email_filtering
Machine learning problem
In machine learning, a probabilistic classifier is a classifier that is able to predict, given an observation of an input, a probability distribution over
Probabilistic_classification
Automated recognition of patterns and regularities in data
estimated from the collected dataset. Note that the usage of 'Bayes' rule' in a pattern classifier does not make the classification approach Bayesian. Bayesian
Pattern_recognition
Concept in statistics
Bayes classifier. The main difference is that in LCA, the class membership of an individual is a latent variable, whereas in Naive Bayes classifiers,
Latent_class_model
Topics referred to by the same term
has a very high time- or memory complexity Naive Bayes classifier, a simple probabilistic classifier Naive set theory, a non-axiomatic approach to set
Naive_(disambiguation)
Data loss prevention solution
of trained sentences and native language processor integrated Naive Bayes classifier were claimed to be included. "MyDLP License". MyDLP Development Team
MyDLP
Type of diagnosis assisted by computers
Rule (e.g. k-nearest neighbors) Minimum distance classifier Cascade classifier Naive Bayes classifier Artificial neural network Radial basis function network
Computer-aided_diagnosis
Estimate of an unobservable underlying probability density function
the class-conditional marginal densities of data when using a naive Bayes classifier, which can improve its prediction accuracy. Frequency distribution
Density_estimation
Quantitative measurement of accuracy
Evaluation of a binary classifier typically assigns a numerical value, or values, to a classifier that represent its accuracy. An example is error rate
Evaluation of binary classifiers
Evaluation_of_binary_classifiers
algorithm Bayes classifier Bayes error rate Bayes estimator Bayes factor Bayes linear statistics Bayes' rule Bayes' theorem Evidence under Bayes theorem
List_of_statistics_articles
Free web-based application to evaluate DNA variants for their disease-causing potential
Project phyloP phastCons The single results are then assessed by a Naive Bayes classifier which decides whether or not their combined effect might be deleterious
MutationTaster
situations. This independence is the "naive" assumption of a Naive Bayes classifier, where properties that imply each other are nonetheless treated as
Binary_independence_model
Hyperparameter optimization framework
PMID 18200004. Yang, Feng-Jen (2018-12-12). "An Implementation of Naive Bayes Classifier". 2018 International Conference on Computational Science and Computational
Optuna
Predictive model interchange format
models including support vector machines, association rules, Naive Bayes classifier, clustering models, text models, decision trees, and different regression
Predictive Model Markup Language
Predictive_Model_Markup_Language
Flow of data across the Internet
an increase in accuracy of the Naive Bayes classifier technique. The basis of categorizing work is to classify the type of Internet traffic; this is
Internet_traffic
into the target categories using synonym based classifier or statistical classifiers, such as Naive Bayes (NB) and Support Vector Machines (SVMs). The meanings
Web_query_classification
Method of estimating the parameters of a statistical model
function-space applications. In the context of Bayes estimators, the MAP can be recovered as the minimizer of the Bayes risk with risk function L ( θ , a ) = {
Maximum a posteriori estimation
Maximum_a_posteriori_estimation
Tree-based ensemble machine learning methods
complex classifier (a larger forest) gets more accurate nearly monotonically is in sharp contrast to the common belief that the complexity of a classifier can
Random_forest
Engineering formula
forest, gradient boosting trees, random forest regression, and naive Bayes classifier. In this type model usually, the deterioration is predicted using a
Deterioration_modeling
Set of methods for supervised statistical learning
the maximum-margin hyperplane and the linear classifier it defines is known as a maximum-margin classifier; or equivalently, the perceptron of optimal
Support_vector_machine
Qualitative data analysis software
cluster analysis. on document-level: Searching, clustering, and Naive Bayes classifier KH Coder allows for further search and statistical analysis functions
KH_Coder
Pattern-recognition performance metrics
connected by Bayes' theorem. The probabilistic interpretation allows to easily derive how a no-skill classifier would perform. A no-skill classifier is defined
Precision_and_recall
Locality-Sensitive Hashing (LSH) Logistic regression Max-Kernel Search Naive Bayes Classifier Nearest neighbor search with dual-tree algorithms Neighbourhood Components
Mlpack
Analyst used Naïve Bayes classifier to perform its predictions. The current version of Proteome Analyst uses Support Vector Machine classifiers. Currently Proteome
Proteome_Analyst
Machine reading of unstructured documents
expressions (or nested group of regular expressions) Using classifiers Generative: naïve Bayes classifier Discriminative: maximum entropy models such as Multinomial
Information_extraction
Algorithmic library developed by Intel
algorithms in this area, including Naïve Bayes classifier, Support Vector Machine, and multi-class classifiers. Recommendation systems Neural networks
Data_Analytics_Library
Computer-based method for summarizing a text
news domain. The system was based on a hybrid system using a Naive Bayes classifier and statistical language models for modeling salience. Although the
Automatic_summarization
K-nearest neighbor algorithm Kernel methods Support vector machine Naive Bayes classifier Artificial neural networks Network topology – Arrangement of a communication
Outline of artificial intelligence
Outline_of_artificial_intelligence
by looking for certain keywords, vocabulary, and style via a naive Bayes classifier returns the name of a popular writer the sample most closely resembles
I_Write_Like
Method of machine learning
implementations of algorithms for Classification: Perceptron, SGD classifier, Naive bayes classifier. Regression: SGD Regressor, Passive Aggressive regressor.
Online_machine_learning
reduction of high-dimensional data Naive Bayes classifier: a family of probabilistic classifiers based on Bayes' theorem Neural Network Backpropagation:
List_of_algorithms
Ambiguous term in statistics
transforming classifier scores into class membership probabilities in the two-class case: Assignment value approach, see Garczarek (2002) Bayes approach,
Calibration_(statistics)
Smooth approximation of one-hot arg max
softmax regression), multiclass linear discriminant analysis, naive Bayes classifiers, and artificial neural networks. Specifically, in multinomial logistic
Softmax_function
Recognition of events from videos or sensors
field Gesture recognition Hidden Markov model Motion analysis Naive Bayes classifier Support vector machines Object co-segmentation Outline of artificial
Activity_recognition
Overview of and topical guide to algorithms
forest Support vector machine k-nearest neighbors algorithm Naive Bayes classifier Gradient boosting Artificial neural network Backpropagation Cluster
Outline_of_algorithms
Statistics concept
The classifier should furthermore be able to adapt to its user and to learn from experience. Starting from an initial standard setting, the classifier should
Bayesian_programming
Textual emotion detection method
The classifier can extract target-specified comments and gathering opinions made by one particular entity. Complex question answering. The classifier can
Sentiment_analysis
Grammar of the Vietnamese language
distinct from the classifier cái that classifies inanimate nouns (although it is historically related to the classifier cái). Thus, classifier cái cannot modify
Vietnamese_grammar
List of concepts in artificial intelligence
links naive Bayes classifier In machine learning, naive Bayes classifiers are a family of simple probabilistic classifiers based on applying Bayes' theorem
Glossary of artificial intelligence
Glossary_of_artificial_intelligence
Algorithm for supervised learning of binary classifiers
perceptron is an algorithm for supervised learning of binary classifiers. A binary classifier is a function that can decide whether or not an input, represented
Perceptron
Mathematical model used for classification or regression
Mitchell, Tom M. (2015). "3. Generative and Discriminative Classifiers: Naive Bayes and Logistic Regression" (PDF). Machine Learning. Ng, Andrew Y
Discriminative_model
Statistical measure of association for two binary variables
classifier that distinguishes between cats and dogs is trained, and we take the 12 pictures and run them through the classifier, and the classifier makes
Phi_coefficient
Technique for the generative modeling of a continuous probability distribution
}}_{t}}}>0} is always true. Classifier guidance was proposed in 2021 to improve class-conditional generation by using a classifier. The original publication
Diffusion_model
high-dimensional space and hence the classifier in the original space. The least-squares version of the SVM classifier is obtained by reformulating the minimization
Least-squares support vector machine
Least-squares_support_vector_machine
existing classifiers, such as the k-Nearest Neighbors, or the naïve Bayes classifier. Using annotated audio data, machines learn to identify and classify the
Audio_mining
Problem in machine learning and statistical classification
nearest neighbours is considered the output class label. Naive Bayes is a successful classifier based upon the principle of maximum a posteriori (MAP). This
Multiclass_classification
Concept in machine learning
{x}}))} and is thus optimal under the Bayes decision rule. A Bayes consistent loss function allows us to find the Bayes optimal decision function f ϕ ∗ {\displaystyle
Loss functions for classification
Loss_functions_for_classification
Geographic areas of indigenous languages
morphology Noun-classifier systems are also common across Amazonian languages. Derbyshire & Payne (1990) list three basic types of classifier systems. Numeral:
Linguistic areas of the Americas
Linguistic_areas_of_the_Americas
British statistician
detection: a review. Statistical Science, 17, 235-255 Hand D.J. (2006) Classifier technology and the illusion of progress (with discussion). Statistical
David_Hand_(statistician)
Set of probability measures
needed] Imprecise probability Dempster–Shafer theory Probability box Robust Bayes analysis Upper and lower probabilities Levi, Isaac (1980). The Enterprise
Credal_set
Dividing things between two categories
classification is binary regression. When measuring the accuracy of a binary classifier, the simplest way is to count the errors. But in the real world often
Binary_classification
System to identify an author
Algorithms used in author profiling include: Support Vector Machines Naive Bayes classifiers Deep averaging networks, many layers in a cycle of machine learning
Author_profiling
Subfield of machine learning
exact optimization algorithm used to train another learner neural network classifier in the few-shot regime. The parametrization allows it to learn appropriate
Meta-learning (computer science)
Meta-learning_(computer_science)
winnowTag uses Winnow content recommendation, a Naive Bayes text classifier evolved from SpamBayes. Users of winnowTag create and share tags, and use the
WinnowTag
British-American computer scientist
networks (with coverage of inference, structure learning, and naive Bayes classifiers), non-parametric methods such as instance-based learning, and efficient
Andrew_W._Moore
Identification of which sense of a word is being used
instrument). The seeds are used to train an initial classifier, using any supervised method. This classifier is then used on the untagged portion of the corpus
Word-sense_disambiguation
representation of the data. Decision trees, neural networks, or a naive Bayes classifier could be used in combination with measures of model quality such as
Multifactor dimensionality reduction
Multifactor_dimensionality_reduction
United States military prison in southeastern Cuba
Guantanamo Bay detention camp is a United States military prison within Naval Station Guantanamo Bay (NSGB), on the coast of Guantánamo Bay, Cuba. It was
Guantanamo_Bay_detention_camp
PMID 23459794. Kohavi, Ron (1996). "Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid". KDD. 96. Oza, Nikunj C., and Stuart Russell
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Adaptive boosting based classification algorithm
harder-to-classify examples. AdaBoost refers to a particular method of training a boosted classifier. A boosted classifier is a classifier of the form
AdaBoost
Categorization of computer network traffic
inter-arrival times. Very often uses Machine Learning Algorithms, as K-Means, Naive Bayes Filter, C4.5, C5.0, J48, or Random Forest Fast technique (compared to deep
Traffic_classification
Branch of statistics mathematics
PMC 3443537. PMID 22670567. Dai, X; Müller, HG; Yao, F. (2017). "Optimal Bayes classifiers for functional data and density ratios". Biometrika. 104 (3): 545–560
Functional_data_analysis
Logic error due to ignoring the base rate
explicitly re-introduced using Bayes' theorem. Precision and recall Data dredging – Misuse of data analysis Evidence under Bayes' theorem Inductive argument –
Base_rate_fallacy
BAYES CLASSIFIER
BAYES CLASSIFIER
Surname or Lastname
English
English : patronymic from Bay.
Surname or Lastname
English
English : patronymic from Bate (see Bartholomew).Americanized form of German Betz. See also Betts.
Surname or Lastname
English
English : unexplained.variant of Spanish Rayas.Muslim : variant of Rais.
Surname or Lastname
English
English : variant spelling of Baines.
Boy/Male
American, Australian, British, English, Irish
From the Hedged Place; Surname
Surname or Lastname
English and Dutch
English and Dutch : variant spelling of Bay.
Boy/Male
English Shakespearean
often used as a surname.
Surname or Lastname
English
English : patronymic from the personal name May (see May).
Boy/Male
American, British, English, Shakespearean
Ploughman; Variant of Bartholomew Often Used as a Surname
Boy/Male
Anglo Saxon
From Ban.
Surname or Lastname
English
English : variant spelling of Bailes.
Surname or Lastname
English (chiefly Yorkshire)
English (chiefly Yorkshire) : variant spelling of Boyce.Americanized spelling of French Bois.
Boy/Male
Irish American English
Surname.
Surname or Lastname
English (East Midlands)
English (East Midlands) : variant of Bayes.
Surname or Lastname
Irish
Irish : reduced Anglicized form of Gaelic Ó hAodha ‘descendant of Aodh’, a personal name meaning ‘fire’ (compare McCoy). In some cases, especially in County Wexford, the surname is of English origin (see below), having been taken to Ireland by the Normans.English : habitational name from any of various places, for example in Devon and Worcestershire, so called from the plural of Middle English hay ‘enclosure’ (see Hay 1), or a topographic name from the same word.English : habitational name from any of various places, for example in Dorset, Greater London (formerly in Kent and Middlesex), and Worcestershire, so called from Old English hǣse ‘brushwood’, or a topographic name from the same word.English : patronymic from Hay 3.French : variant (plural) of Haye 3.Jewish (Ashkenazic) : metronymic from Yiddish name Khaye ‘life’ + the Yiddish possessive suffix -s.U.S. President Rutherford B. Hayes (1822–1893), born in Delaware, OH, was descended from old New England families on both sides. Through the paternal line he was descended from George Hayes, who emigrated from Scotland in 1680 and settled in Windsor, CT.
Surname or Lastname
English (Lancashire)
English (Lancashire) : variant spelling of Hayes.
Surname or Lastname
English
English : patronymic from the Middle English personal name Baye (see Bay).
Surname or Lastname
English
English : variant spelling of Bailes.Czech (Baleš) and Slovak (Báleš) : from a pet form of Bal, a shortened form of the personal name Baltazar.
Surname or Lastname
Czech and Slovak (Bareš)
Czech and Slovak (Bareš) : from a pet form of the personal name Bartoloměj (see Bartholomew).German : probably from a Germanic personal name based on bero ‘bear’English : unexplained; perhaps a variant of Barrs or Barras.Galician : habitational name from Bares in A Coruña province.
Surname or Lastname
English
English : patronymic from Kay 5.
BAYES CLASSIFIER
BAYES CLASSIFIER
Girl/Female
Indian
Peace
Girl/Female
Tamil
Aanandamayi | ஆநஂதமயீ
One with full of happiness
Male
Japanese
(真二) Japanese name SHINJI means "true second (son)."Â
Boy/Male
Bengali, Hindu, Indian, Kannada, Malayalam, Marathi, Mythological, Tamil
Fifth Incarnation of Lord Vishnu
Girl/Female
Arabic, French, Indian, Muslim, Tamil
Pretty Girl; Beautiful Woman; Beauty
Boy/Male
American, British, English
From the Bank
Boy/Male
Greek
Calling forth.
Girl/Female
Gujarati, Hindu, Indian, Kannada, Sindhi, Telugu
Earth
Surname or Lastname
Korean
Korean : there is one Chinese character for the Son surname. Some sources mention as many as 118 clans for the Son family, but only seven can be documented. According to legend, the Son clan’s founding ancestor was named Kuryema and was one of the six pre-Shilla elders who made Pak HyÅkkÅse the first king of Shilla. The first documented ancestor, however, was called Sun. Sun is said to have lived a poverty-stricken existence in the Shilla period. His son was a voracious eater and ate Sun’s old mother’s food as well as his own. Sun, feeling that he could always get another son but that his mother was irreplaceable, decided to go into the mountains to bury his son. When he dug into the ground, however, he found a bell. He hung the bell on a nearby tree and rang it. So loud and clear was the cry of the bell that the king heard it in the palace below and came to investigate. The king was amazed at the bell and gave Sun a house and food. Later, a Buddhist temple was built on that spot. The founding ancestor of the Iljik (or Andong) Son clan originally bore the surname Sun, but during the reign of KoryÅ king HyÅnjong (1009–1031), Sun was changed to Son.English : from Middle English sone ‘son’, hence a distinguishing epithet for a son who shared the same personal name as his father.Jewish (Ashkenazic) : variant of Sohn, or Sonn.
Boy/Male
Australian, Hindu, Indian
Law; Rule
BAYES CLASSIFIER
BAYES CLASSIFIER
BAYES CLASSIFIER
BAYES CLASSIFIER
BAYES CLASSIFIER
a.
Situated under, or at the bases of, the lobules of the liver.
n.
Wearing, or protected by, bases.
pl.
of Basis
imp. & p. p.
of Bay
n.
One of several isomeric organic bases of the quinoline series of alkaloids.
n.
The player stationed in the field bewtween the second and third bases.
n.
A solid body resembling a right cylinder, but having the bases or ends elliptical.
n.
any one of a series of nitrogenous bases, certain of which are used as antipyretics.
v. i.
To make up packs, bales, or bundles; to stow articles securely for transportation.
n.
Packs or bales of Spanish wool.
n.
Either of two metameric nitrogenous hydrocarbon bases, C12H8N2, analogous to phenanthridine, but more highly nitrogenized.
n.
Alt. of Bayze
n.
A five-pointed star, resembling five alphas joined at their bases; -- used as a symbol.
v. i.
To do the work of baking something; as, she brews, washes, and bakes.
a.
Related to, or formed from, pyridin or its homologues; as, the pyridic bases.
n.
An affirmative vote; one who votes in the affirmative; as, "To call for the ayes and noes;" "The ayes have it."
n.
One of the branchiae attached to the bases of the legs in Crustacea.
v. t.
A song to quiet babes or lull them to sleep; that which quiets.
a.
Having a bay or bays.
v. i.
To be baked; to become dry and hard in heat; as, the bread bakes; the ground bakes in the hot sun.