Classifier options greyed out in Weka [closed] - machine-learning

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Closed 9 years ago.
I have numeric data which has missing values. I want to classify the data using Naive Bayes Classifier in Weka but the option is grayed out. Please help.

If a classifier is grayed out, it means that it doesn't support the kind of task you want to do. This could be because of the type of features or because of the type of predictions you want to make.
In your case it could be that you're trying to predict a numeric instead of a categorical attribute.

Related

How to Classify Data In Opencv [closed]

It's difficult to tell what is being asked here. This question is ambiguous, vague, incomplete, overly broad, or rhetorical and cannot be reasonably answered in its current form. For help clarifying this question so that it can be reopened, visit the help center.
Closed 9 years ago.
I have 130 objects.Each object is defined by 13 points(2-d points),these 13 points form data_unit. Thus there are 130 data_units. I want to classify these data_units into 4 classes. How can we do this.k-means is not possible in this scenario what are the alternatives.
There is a whole set of classification methods based on technique called machine learning. The ones implemented in OpenCV are described here. You can try for example Support Vector Machines. Its a nice and fairly easy in use method, with some tricks to get past data that cannot be linearly separated.

Is taking surveys by random people supervised or unsupervised learning? [closed]

It's difficult to tell what is being asked here. This question is ambiguous, vague, incomplete, overly broad, or rhetorical and cannot be reasonably answered in its current form. For help clarifying this question so that it can be reopened, visit the help center.
Closed 10 years ago.
I have a list of cities like London, Paris, Roma etc.
I want to return which cities are interesting based on some features. I asked people to judge whether they find those cities interesting or not. I show each city with the average of people's judgement of how interesting it is.
Is this supervised or unsupervised learning?
This is supervised learning.
Supervised learning is when your training set consists of both the input data and the desired output data. In this case, the input data is the cities and the output data is the ratings that the people have given it.
What you are suggesting is a recommender system; these can be built using a technique called collaborative filtering.

Mahout for unstructured data an advantage? [closed]

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Closed 10 years ago.
I have installed mahout and test run several examples; would it be safe to say that one of Mahout's advantages it being used for unstructured data (scalability aside)?
No... most of the algorithms take fairly specifically structured input like vectors or user-item pairs. There are some tools for vectorizing text docs which are unstructured. But no I wouldn't call it a tool primarily for unstructured data.

What recommended machine learning libriries to use? [closed]

It's difficult to tell what is being asked here. This question is ambiguous, vague, incomplete, overly broad, or rhetorical and cannot be reasonably answered in its current form. For help clarifying this question so that it can be reopened, visit the help center.
Closed 10 years ago.
I used Mahout, it is great , but need something better that have more implemented algorithms and maybe faster
On the OS side there's WEKA, with a large collection of algorithms across learning disciplines.

Check sum calculation [closed]

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Closed 11 years ago.
I am new to know about check sum. So kindly help me.
I have these four binary values and i need to calculate the check sum for these numbers.
They are
0111011101100
1011011000110
0011011011110
1011010110010
I really don't know the algorithm to calculate these values. Can somebody shed a light on this. Whats the final checksum for these four values.
There is no "the checksum". There are many algorithms for "checksum" calculation. CRC32, Adler32, in a certain way as well MD4, MD5, SHA1, other SHA algorithms, etc.

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