Which of the following is a major disadvantage of using a neural network?

Arguably, the best-known disadvantage of neural networks is their “black box” nature. Simply put, you don’t know how or why your NN came up with a certain output.

What are the disadvantages of neural networks?

Disadvantages of Artificial Neural Networks (ANN)

  • Hardware Dependence: …
  • Unexplained functioning of the network: …
  • Assurance of proper network structure: …
  • The difficulty of showing the problem to the network: …
  • The duration of the network is unknown:

What are advantages and disadvantages of using neural networks?

The network problem does not immediately corrode. Ability to train machine: Artificial neural networks learn events and make decisions by commenting on similar events. Parallel processing ability: Artificial neural networks have numerical strength that can perform more than one job at the same time.

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What is a major drawback of the neural network modeling?

Disadvantages include its “black box” nature, greater computational burden, proneness to overfitting, and the empirical nature of model development. An overview of the features of neural networks and logistic regression is presented, and the advantages and disadvantages of using this modeling technique are discussed.

What are the disadvantages in using a neural network to build a supervised model?


  • Neural networks are black boxes, meaning we cannot know how much each independent variable is influencing the dependent variables.
  • It is computationally very expensive and time consuming to train with traditional CPUs.
  • Neural networks depend a lot on training data.

What is a disadvantage of a network?

Purchasing the network cabling and file servers can be expensive. There is a danger of hacking , particularly with wide area networks. … Security procedures are needed to prevent such abuse, eg a firewall .

What is the biggest problem with neural networks?

The very most disadvantage of a neural network is its black box nature. Because it has the ability to approximate any function, study its structure but don’t give any insights on the structure of the function being approximated.

Which of the following are the disadvantages of using Knn?

Some Disadvantages of KNN

  • Accuracy depends on the quality of the data.
  • With large data, the prediction stage might be slow.
  • Sensitive to the scale of the data and irrelevant features.
  • Require high memory – need to store all of the training data.
  • Given that it stores all of the training, it can be computationally expensive.
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What are the disadvantages of deep learning?

Drawbacks or disadvantages of Deep Learning

➨It requires very large amount of data in order to perform better than other techniques. ➨It is extremely expensive to train due to complex data models. Moreover deep learning requires expensive GPUs and hundreds of machines. This increases cost to the users.

What is neural network and its advantages?

Advantages of Neural Networks:

Neural Networks have the ability to learn by themselves and produce the output that is not limited to the input provided to them. The input is stored in its own networks instead of a database, hence the loss of data does not affect its working.

What are the appropriate problems for neural network learning?

Appropriate Problems for ANN

  • training data is noisy, complex sensor data.
  • also problems where symbolic algos are used (decision tree learning (DTL)) – ANN and DTL produce results of comparable accuracy.
  • instances are attribute-value pairs, attributes may be highly correlated or independent, values can be any real value.

What are the drawbacks of machine learning?

Disadvantages of Machine Learning

  • Possibility of High Error. In ML, we can choose the algorithms based on accurate results. …
  • Algorithm Selection. The selection of an algorithm in Machine Learning is still a manual job. …
  • Data Acquisition. In ML, we constantly work on data. …
  • Time and Space.

What kind of problems can neural networks solve?

Neural networks can provide robust solutions to problems in a wide range of disciplines, particularly areas involving classification, prediction, filtering, optimization, pattern recognition, and function approximation.

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What are the advantages and disadvantages of decision trees?

Advantages and Disadvantages of Decision Trees in Machine Learning. Decision Tree is used to solve both classification and regression problems. But the main drawback of Decision Tree is that it generally leads to overfitting of the data.

What are the disadvantages of CNN?

Summation of all three networks in single table:

Disadvantages Hardware dependence, Unexplained behavior of the network. Large training data needed, don’t encode the position and orientation of object.

What are the drawbacks of fuzzy logic and neural networks?

A major drawback of Fuzzy Logic control systems is that they are completely dependent on human knowledge and expertise. You have to regularly update the rules of a Fuzzy Logic control system. These systems cannot recognize machine learning or neural networks.

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