Respuesta :

adeelahmedalm

Answer:

Prediction Accuracy of Neural Networks depends upon two key factors

1- Neural modeling framework used

2- Characteristics of data set-Imputed

A neural network is a network of neurons, like a human brain has, or in a current era sense, an artificial neural network, made up of of artificial neurons or nodes. Hence a neural network is a computing system that is inspired by human brain and its nervous system. It is used to solve Artificial Intelligence (AI) problems.

Further Explanation:

• ANN is an adaptive system that adjusts its structure on the basis of external or internal information which flows through the network and this change also depends on the computational model used. Neural Network (NN) or Artificial Neural Network (ANN) prediction accuracy depends upon:

1- Characteristics of Data Set Imputed:

A neural network is a series of algorithms used to recognize underlying relationships in a set of data through a process that resembles the way the human brain processes information.

Neural networks can adjust itself to changing inputs; so the network generates the best possible result without needing to redesign the output requirements.

2- Neural Models:

Neural modeling field is a mathematical framework for machine learning which is based on combining ideas comes  from neural networks, fuzzy logic- a kind  of logic used in computers that are designed to act like humans, and model based recognition.

Practical Application

  • Self driving Cars
  • Business forecasting i.e. planning, demands, supply
  • Pattern-object recognition i.e. face recognition
  • Medical diagnosis

Helpful Links on Neural Networks explanation:

https://brainly.in/question/4226585

https://brainly.in/question/7635118

https://brainly.com/question/10599832

Answer details :

Grade: High School

Subject: Computers and Technology

Key Words:

Machine learning, neural networks, artificial neural networks, artificial intelligence, Neural modeling etc

Answer:

Prediction accuracy of a neural network depends on input and output.

Further Explanation:

Neural network: Neural network are used for mainly deep learning. It has multiple layer of neurons that are used to classify things and make predictions. The neural network consists of input layer, hidden layers and output layers. The prediction of accuracy depends on input as well as output. The prediction process also depends on training process of neural network.

The prediction of neural network depends on the following features:

  1. The method used for neural modeling
  2. The characteristics of data set used
  3. The training process of neural network (For e.g. Fuzzy logic)
  4. Input and Output data

The applications of neural network are listed below:

  • Text Classification and Categorization
  • Part of Speech Tagging
  • Semantic Parsing
  • Paraphrase Detection
  • Machine Translation
  • Speech Recognition
  • Spell Checking

Learn more:  

1. A company that allows you to license software monthly to use online is an example of ? brainly.com/question/10410011  

2. Prediction accuracy of a neural network depends on _______________ and ______________. brainly.com/question/10599832  

3. The shape of our galaxy was determined ‘on the inside looking out' by surveying the milky way using ____________ telescopes. brainly.com/question/7866623  

4. List 3 characteristics of the ideal encryption scheme. https://brainly.com/question/3000161

Answer details:

  • Grade: Computer Engineering
  • Subject: Artificial Intelligence
  • Chapter: neural Network

Keyword:  

Neural network, prediction accuracy, depend, input, output, modeling, training process, artificial neural network, characteristics, data set, Face Recognition, fuzzy logic, deep learning, prediction, input layer, hidden layers, output layers

Otras preguntas