Questions tagged [randomized-algorithms]
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22 questions
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Is it mandatory to set a random_state when using RandomizedSearchCV?
When I use RandomizedSearchCV, if I put the random state I always obtain the same results with the same hyperparams trainer. So, is it mandatory to use? Because in my opinion it is better to always ...
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Clustering by using Locality sensitive hashing *after* Random projection
It is well known that Random Projection (RP) is tightly linked to Locality Sensitive Hashing (LSH). My goal is to cluster a large number of points lying in a d-dimensional Euclidean space, where $d$ ...
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Grid Searching seed in randomized machine learning
I was wondering if tuning a seed with cross-validation in order to maximize the performance of an algorithm heavily based on a randomness factor is a good idea or not. I have created an Extra Tree ...
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Create a random chi-Square independence distribution with a given p-Value
I want to randomly create a table of data that has a predefined p-Value and chi-Value of a chi-square distribution.
For example this would have a p-Value of 1 on a chi-square independence test:
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What is the objective that is optimized with Random Search?
I have recently learned about Random Search (or sklearn.model_selection.RandomizedSearchCV in Python) and was thinking about the theory behind the optimization process. In particular my question is, ...
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Is shuffling data really necessary for training? [duplicate]
I don't mean if we had a dataset where if sequentially sampled, the labels would be [1111122223333]. In this case, the network learns to predict everything as 1, then 2, and so on and it's impossible ...
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How to compute modulo of a hash?
Let's say that I have a set of users in my database, that have GUIDs as their IDs. I use xxhash to generate fixed-length hashes for each value, so that I can then ...
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Cannot clone object <keras.wrappers.scikit_learn.KerasRegressor object at 0x7fdc9c3ba550>
Trying to hypertune ANN but getting an error while using fit..(grid1.fit(X_train, y_train))
Below is the code
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RL Sutton book, initial estimate of q*(a) for 10 arm testbed
The Sutton book does not mention what the initial estimate is for q*(a) before the first reward is received. In this code repo that seems to go along with the book: Sutton code repo
They have ...
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How to generate 12 independent random weights which all add up to one
I'm using Palisade's @Risk software with a triangular distribution to generate 12 random weights which must add up to one, but I get a lot of negative numbers. Is there a straightforward way to set ...
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Why would one crossvalidate the random state number?
Still learning about machine learning, I've stumbled across a kaggle (link), which I cannot understand.
Here are lines 72 and 73:
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Splitting train/test sets by an identifier?
I know sklearn has train_test_split() to split a train and test set. But I read that, even with setting a random seed, if your actual dataset is updated regularly, ...
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What is the most efficient method for hyperparameter optimization in scikit-learn?
An overview of the hyperparameter optimization process in scikit-learn is here.
Exhaustive grid search will find the optimal set of hyperparameters for a model. The downside is that exhaustive grid ...
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how to label a tain_data? [closed]
I have one assignment that I have four files
1) train_data.csv: The training file contains two fields (text, id).
2) train_label.csv: The label file contains two fields (id, label).
3) test_data.csv: ...
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How to choose the random seed?
I understand this question can be strange, but how do I pick the final random_seed for my classifier?
Below is an example code. It uses the ...
- 3,608
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contextual bandits for online learning
Which of the algorithms in the current literature for contextual bandits can be implemented for online learning and which ones can't? I'd really appreciate it if someone could provide a link to papers ...
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Epoch greedy algorithm for contextual bandits
I'm reading the following paper on the epoch greedy algorithm for the contextual bandits problem. I have two questions
http://hunch.net/~jl/projects/interactive/sidebandits/bandit.pdf
I'm unsure ...
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Testing Multi-Arm Bandits on Historical Data
Suppose I want to test a multi-arm bandit algorithm in the contextual setting on a set of historical data. For simplicity, let's assume there are only two arms A and B and suppose the rewards are ...
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Multi-arm bandit problem for bernoulli reward distribution
Suppose in the multi-arm bandit problem I know my rewards are distributed as $0$ or $1$ i.e according to a Bernoulli distribution rather than the condition that they lie in the range $[0,1]$. Does ...
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Why should the initialization of weights and bias be chosen around 0?
I read this:
To train our neural network, we will initialize each parameter W(l)ijWij(l) and each b(l)ibi(l) to a small random value near zero (say according to a Normal(0,ϵ2)Normal(0,ϵ2) ...
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HOW TO: Deep Neural Network weight initialization
Given difficult learning task (e.g high dimensionality, inherent data complexity) Deep Neural Networks become hard to train.
To ease many of the problems one might:
Normalize && handpick ...
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Interpreting the results of randomized PCA in scikit-learn
I'm using scikit-learn to do a genome-wide association study with a feature vector of about 100K SNPs. My goal is to tell the biologists which SNPs are "interesting".
RandomizedPCA really improved ...
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