Data Mining & Data Ware House
Data Mining & Data Ware House
1. Adaptive system management is
- It uses machine-learning techniques.Here program can learn from past experienceand adapt themselves to new situations
- Computational procedure that takes some value as inut and produces some value as output
- Science of making machines performs tasks that would require intelligence when performed by humans
- None of these
2. Algorithm is
- It uses machine-learning techniques Here program can learn from past experience and adapt themselves to new situations
- Computational procedure that takes some value as input and produces some value as input and produces some value as output
- Science of making machines performs tasks that would require intelligence when performed by humans
- None of these
3. Background knowledge referred to
- Additional acquaintnce used by a learning algorithm to facilitate the learning process
- A neural network network that makes use of a hidden layer.
- It is form of automatic learning.
- None of these
4. Back propagation networks is
- Additional acquaintance used by a learning algorithm to facilitate the learning algorithm to faclilitate the learning process
- A neural network that makes use of a hidden layer
- it is a form of automatic learning.
- None of these
5. Bayesian classifers is
- A class of learning algorithm that tries to find an optimum classfication of a set of examples using the probabilistic theory
- Any mechanism employed by a learning system to constrain the search space of a hypothesis
- An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experience, adapting the explanations to fit the new situation.
- None of these
6. Bias is
- A class of learning algorithm that tries to find an optimum classfication of a set of examples using the probabilistic theory
- Any mechanism employed by a learning system to constrain the search space of a hypothesis
- An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation.
- None of these
7. Case-based learning is
- A class of learning algorithm that tries to find an optimum classfication of a set of examples using the probabilistic theory
- Any mechanism employed by a learning system to constrain the search space of a hypothesis.
- An approach to the design of learning algorithm that is inspired by the fact that when people encounter new situations. They often explain them by reference to familiar experiences, adapting the explanations to fit the new situation.
- None of these
8. Binary attribute are
- This takes only two values. in general, these values will be 0 and 1 they can be coded as one bit
- The natural environment of a certain species
- Systems that can be used without knowledge of internal operations
- None of these
9. Biotope are
- This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit.
- The natural environment of a certain species
- Systems that can be used without knowledge of internal operations
- None of these
10. Black boxes
- This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit.
- The natural environment of a certain species
- Systems that can be used without knowledge of internal operations
- None of these