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Results tagged with machine-learning
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user 141356
Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.
2
votes
Accepted
Which attribute to choose first (the root) when making a decision tree?
ID3 algorithm would first takes growling because creates two nodes that are overall purer than the root:
root has 3 yes and 5 no, if you use growling to split your data you'll have 2 yes and 2 no in o …
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2
votes
Accepted
Proving that a function is not a kernel function
$k(\cdot, \cdot)$, depending on the first term, may be any positive number, and is independent on the second term, hence kernel matrix $K$ can be any matrix having equal positive values whitin rows.
T …
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1
vote
Application of Classical Multidimensional Scaling in Matlab on new data
If you do MDS on two different data sets, you get different subspaces of your original data space. If you train a ML model on one subspace, there is no reason to believe that same model would even wor …
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1
vote
How to identify the most impactful features in a ML model, i.e. the predictor variables that...
What you want is actually feature importance. The method scikit-learn uses for evaluating it is pretty basic: it sums up the training score gain of all the splits made in all trees using each variable …
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2
votes
Loss function for regression with uncertain labels
Usual approach in statistics is to consider the errors $\epsilon_i= y_i-E[y_i|x]$ homoscedastic with variance $\sigma^2$. This assumption, joint with independence one, results in least squares as the …
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1
vote
RBF kernel mapping
for x of any dimension:
we know that $\phi (x_1) \cdot \phi (x_2) = k(x_1, x_2)$, so, it's clear that $||\phi(x)||^2 = k(x, x)$. we can now try to find the norm of generic $\phi(x)$ and, if we find …
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3
votes
Accepted
How to interpret a hierarchical clustering dendrogram?
The higher branch is a cluster including all the genes that you can see below in that branch. The height of a node is the distance between the two subclusters/subbranches (how that distance is compute …
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3
votes
Why does machine learning work for high-dimensional data($n \ll p$)?
One word: regularization. The complexity of a model is indeed more or less proportional to the number of predictors (this depends on the model), but ML algorithms use regularization to split the predi …
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3
votes
Accepted
Finding similarity between two datasets
1) almost so.
The proportions can be considered as conditional probability of finding a white person, when looking for someone randomnly in each state. You may then define a joint probability function …
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5
votes
Problems, which are difficult for SGD
Second order methods use more information about the loss function (it computes two orders of derivative instead of only one), and so it approximates it better and has a better convergence.
It doesn't …
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4
votes
1
answer
667
views
Classification of data tables (each table is an item)
I have to work on a binary classification task where single items to be classified are not single rows of a data matrix, but groups of rows. In other words, I have $N$ data tables of varying size $n_i …
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5
votes
XGBoost - Can we find a "better" objective function than RMSE for regression?
does the same logic hold true for gradient boosted trees?
Yes, by any mean. Gradient boosting can be used to minimize any sensible loss function, and it is very effective in doing it.
It is worth sa …
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1
vote
How to find similarity in R or Python?
For comparison, you should create a contingency matrix with table(df$shop, df$book_id) (but you may want to use a tool like xtabs instead, to create a sparse matrix from package Matrix). Then, you can …
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1
vote
Accepted
How to balance transformation decisions, feature selection, and model tuning vs time in text...
You can do one of three things:
try different approaches still, like RNNs, CNNs, word vectorization... depending on your sample size and on your problem, they can be quite beneficial
make an ensemble …
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3
votes
0
answers
1k
views
R alternative to scikit-learn [closed]
As a statics researcher, I've been using R since university and I know it quite well, I also know that it's immediate, but it quickly gets chaotic, and this also happens because of the variety and inc …