What is Accuracy

1.

The proportion of the total number of predictions that are correct. Learn more in: Systematic Literature Review: XAI and Clinical Decision Support

2.

AI and ML technology use algorithms to analyze data and make predictions based on that information. Although reports indicate that AI programs can be at least 95% accurate on a regular basis, AI programs cannot determine whether or not the data being analyzed is accurate, so usually overall accuracy is much lower but normally higher than 80%. Learn more in: How Can Education Use Artificial Intelligence?: A Brief History of AI, Its Usages, Its Successes, and Its Problems When Applied to Education.

3.

It is a metric used to predict the correctness of a machine learning model. The model is trained using the train data and a classifier is built. The test data is used to cross validate the classifier model. The percentage of correctly classified instances is termed as accuracy. Learn more in: Machine Learning in Python: Diabetes Prediction Using Machine Learning

4.

Area of information control dealing with the correctness of information or lack of errors in information. Learn more in: RFIDs and the Changing Marketplace

5.

Accuracy is defined as the nearness of a measurement to the standard or true value i.e., a highly accurate navigation system will provide measurements very close to the standard, true or known values. A rigorous statement of accuracy includes statistical measures of uncertainty and variation. Accuracy is generally represented by standard deviation of errors (difference between measurements on the map and the true value). Learn more in: Map Matching Algorithms for Intelligent Transport Systems

6.

Parameter that represents the number of individuals correctly diagnosed among a given group, by a clinician or decision support system. Learn more in: Towards an Effective Imaging-Based Decision Support System for Skin Cancer

7.

In classification, it one of the metric to evaluate the classification model and defined as: Accuracy=(Number of correct predictions)/(Total number of predictions). Learn more in: Heart Disease Diagnosis: A Machine Learning Approach

8.

the parameter for evaluating the performance of the machine or models which finds that how much the measured results are near to the actual value. Accuracy calculate all the correct prediction observation divided by the total observation number or actual number. Learn more in: Insulin DNA Sequence Classification Using Levy Flight Bat With Back Propagation Algorithm

9.

Refers to the degree of closeness between a measurement and its accepted or true value. Learn more in: A Hybrid Classification Algorithm and Its Application on Four Real-World Data Sets

10.

It is the ratio for the total correct predicted values to the addition of total correct predicted values and total incorrectly predicted values. Learn more in: Question Answering Chatbot Using Memory Networks

11.

Error measure for assessing the quality of a prediction (classification) which corresponds to the proportion of correctly predicted test cases to all test cases. Learn more in: Predicting Estimated Arrival Times in Logistics Using Machine Learning

12.

The difference between the real and calculated user position. Learn more in: Computer Modelling of Autonomous Satellite Navigation Characteristics on Geostationary Orbit

13.

A measurement that gives the closeness of the measured value to the true value. Learn more in: Customer Churn Reduction Based on Action Rules and Collaboration

14.

The degree of proximity of a measurement in relation to the target true value. Sometimes called “trueness”, it is often confounded with “precision” which refers to the variability of the results within one set of measurement. Learn more in: A Preliminary Framework to Fight Tax Evasion in the Home Renovation Market

15.

One minus error percentage. Learn more in: Data Mining Applications in a Medical System: A Case Study

16.

The degree of conformity of a measured or calculated quantity to its actual (true) value. Accuracy is the degree of veracity. Learn more in: Geometric Quality in Geographic Information

17.

Rate of valid model predictions using a dataset. Accuracy is generally assessed using an independent test set that was not used throughout the study procedure at any point. Cross-validation and bootstrapping, particularly with a small number of datasets, are often employed alongside more complicated precision estimations approaches. Learn more in: Privacy Preservation of Image Data With Machine Learning

18.

The number of correct prediction divided by the total number of predictions. Learn more in: Statistical Hypothesization and Predictive Modeling of Reactions to COVID-19-Induced Remote Work: Study to Understand the General Trends of Response to Pursuing Academic and Professional Commitments

19.

The proportion of all data points that were correctly predicted. It is the ratio of true positives and true negatives to false positives, false negatives, and true positives, divided by all of these. Learn more in: Brain Tumor Segmentation Using Deep Learning Technique: 2D U-Net Model Variant for Tumor Segmentation

20.

The percentage of both passed students and failed students combined predicted accurately. Learn more in: Development of Accurate and Timely Students' Performance Prediction Model Utilizing Heart Rate Data

21.

It is defined as the deviation of calculated value from its target value. Learn more in: Realizing the Need for Intelligent Optimization Tool

22.

Accuracy is percentage of correctly classified normal as well as abnormal samples out of total samples, and it is given by the ratio of addition of true positive and true negative samples to the total number of samples under test. Learn more in: Algorithms for Detection and Classification of Abnormality in Mammograms: An Overview

23.

The performance metric for classifiers indicating the percentage of correctly classified cases regardless of the class to which they belong. Learn more in: Best Practices in Dropout Prediction: Experience-Based Recommendations for Institutional Implementation

24.

This refers to ability of something, especially transaction, being exact, accurate without any error Learn more in: Determinants of E-Government Satisfaction: The Case Study of E-Procurement

25.

A data quality dimension that reflects the confirmation of data items to a baseline that is perceived to be correct, and the extent to which conflicts with the correct baseline affects fitness to use. A baseline could be, for example, the real-world value that a data item reflects, a value in another dataset that was reliably validated, or a targeted calculation result. Learn more in: Measuring Data Quality in Context

26.

Accuracy is defined as the ratio of the total number of correct predictions to the summation of the total number of correct predictions and the total number of incorrect predictions. Learn more in: Video-Based Human Authentication System for Access Control

27.

It has been described in terms of people's capacity to actively manage personal data. But making people responsible for their own information would dramatically restrict what can be considered private. Learn more in: The Ethical Consideration of Using Artificial Intelligence (AI) in Medicine

28.

The ratio of the number of the outputs correctly predicted by the algorithm to the total number of predictions Learn more in: Analytics of User Behaviors on Twitter Using Machine Learning

29.

Correct or precise. Learn more in: Moving Beyond the Textbook to Reframe Disciplinary Literacy Using Text Sets: Content Area Literacy for Pre-Service Teachers

30.

Accuracy is a percentage of correctly classified normal as well as abnormal samples out of total samples. It is given by the ratio of the addition of True Positive and True Negative samples to the total number of samples under test. Accuracy = TP+TN/TP+FP+FN+TN. Learn more in: Text Separation From Document Images: A Deep Learning Approach

31.

Is a metric used to estimate the performance of a classification system .Accuracy is defined as the number of correct predictions divided by the total number of input samples. Learn more in: Smart Farming: Automatic Detection and Classification of Olive Leaf Diseases

32.

It is the measurement used to determine which model is best at identifying relationships and patterns between variables in a dataset based on the input, or training, data. Learn more in: Comprehensive Overview of Autonomous Vehicles and Their Security Against DDoS Attacks

33.

The degree to which a measured value conforms to true or accepted values. Accuracy is a measure of correctness. It is distinguished from precision, which measures exactness. Learn more in: Application of Conventional UAVs for the Identification and Classification of Dense Green Spaces

34.

The quality of being true, exact or fair. Free from error in facts and mistakes. Learn more in: The Biased Truth: An Objective Perspective on Nonobjective News Reporting

35.

A criterion for predictive models calculated by the ratio of correct predictions out of the number of evaluated cases. Learn more in: Creating and Analyzing Induced Decision Trees From Online Learning Data

36.

It is the ratio of number of accurate predictions produced by classification algorithm to the total number of input data samples. Learn more in: Machine Learning and Its Application in Monitoring Diabetes Mellitus

37.

Accuracy is the most native measure of performance evaluation. It is concerned with the closeness of an outcome to the true or actual value. It is a great measure. The high accuracy of a model means that the model is best. Learn more in: Crow-ENN: An Optimized Elman Neural Network with Crow Search Algorithm for Leukemia DNA Sequence Classification

38.

The number of classifications that a model correctly predicts over the total number of predictions. This measure is used to determine the fraction of class predictions that a model got right. Learn more in: Convolutional Neural Networks and Deep Learning Techniques for Glass Surface Defect Inspection

39.

Accuracy is the parameter for evaluating the performance of the machine or models which finds that how much the measured results are near to the actual value. Accuracy calculate all the correct prediction observation divided by the total observation number or actual number. Learn more in: Optimizing Learning Weights of Back Propagation Using Flower Pollination Algorithm for Diabetes and Thyroid Data Classification

40.

Measure of outcome correctness. Measures the proportion of true results (True Positives and True Negatives) among the total number of predictions. Learn more in: Using Data Science to Predict Hotel Booking Cancellations