Characteristics of accuracy. Type of problem it deals

Characteristics of Algorithms

Decision Trees Algorithm

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!


order now

K Nearest Neighbor
Algorithm

Naïve Bayes Algorithm

Space Vector machine Algorithm

Random Forest Algorithm

Neural Network Algorithm

 
 
 
Accuracy

 
The Decision trees have average or moderate level of accuracy

 
The K nearest algorithm (KNN) also has average accuracy level.

 
The Naïve Bayes Algorithm has below average and a very poor accuracy level in general.

 
The space vector machine algorithm has the best overall accuracy.

 
The random forest algorithm has the highest level of accuracy in general.

 
The neural network based algorithms also have a fairly moderate level of accuracy.

 
 
 
 
Type of problem it deals with

 
The decision trees has the capability of dealing and solving both the classification and as well as regression problems

 
The KNN algorithm can also deal with either classification or regression problems

 
The Naïve Bayes Algorithm can specifically deal with only problems of classification.

 
The space vector machine algorithm is fundamentally used for solving both the classification and regression problems.
 

 
The Random forest algorithm can even handle both the
classification and the regression problem

 
The Neural network algorithm can handle either classification or regression problem

 
 
 
 
 
Is it easy to understand the algorithm?

 
The decision trees are neither easy nor difficult to understand and explain to others. The complexity of a decision tree depends on the complexity of a problem
 

 
It is relatively easy to understand a KNN algorithm.

 
The Naive Bayes Algorithm just like decision trees is neither easy nor difficult to understand.

 
The space vector machine algorithm is very easy to learn, understand and implement.

 
The random forest algorithm is very tricky and difficult to understand.

 
The neural network algorithm is also quite difficult to understand.

 
 
 
 
 
Predicting output speed of Algorithm
 

 
It does not take much time to analyze data and predicts.

 
The prediction speed in KNN algorithm depends on the value of
‘n’.

 
This algorithm also does not take much time for making predictions.

 
It performs predictions quickly and does not take much time for analyzing data.

 
The prediction speed of random forest algorithm is relatively moderate, neither too slow nor too fast
 

 
The prediction speed of neural network is fast

 
 
 
the capability of handle noise in data

 
They can moderately tolerate data noise

 
The KNN algorithm has very low tolerance to noise data

 
It has exceptional capability of tolerating noise in data

 
They can moderately tolerate noise in data

 
They can tolerate noise very well up to certain  ration
 

 
They can moderately tolerate noise in data

 
 
 
Capability of handling missing values in given data

 
Its capability of handling missing values in data is relatively good

 
It cannot handle missing values in data

 
It can efficiently handle missing values in the data

 
Its capability of handling missing values in data is average

 
Its capability of handling missing values in data is relatively good
 

 
It cannot handle missing values in data

 
 
Ability to automatically learn from experience

 
They have the ability to learn automatically from past experiences

 
No, they cannot learn automatically.

 
No, they also cannot learn automatically.

 
Yes, it can.

 
Yes, they have the ability to learn automatically from past experiences
 

 
They can learn automatically from past experiences

 
Interpretability

 
Moderately fare

 
It has very low interpretability.
 

 
Low Interpretability

 
Low
Interpretability

 
High level of interpretability

 
Low
Interpretability
 

 
 
Performance capability based on little data observation

 
No, decision trees cannot perform well on the bases of limited data observation
 

 
It cannot perform well.

 
Yes, it can perform very well with only small no of observation.

 
Yes it can perform well

 
No, it cannot perform well

 
No, it cannot perform well

x

Hi!
I'm Harold!

Would you like to get a custom essay? How about receiving a customized one?

Check it out