Questions tagged [randomized-algorithms]

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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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1answer
25 views

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 ...
3
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1answer
194 views

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: ...
3
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1answer
472 views

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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2answers
333 views

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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0answers
26 views

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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2answers
1k views

How to choose the random seed?

I understand this question can be strang, but how do I pick the final random_seed for my classifier? Below is an example code. It uses the ...
0
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1answer
293 views

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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0answers
148 views

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 ...
2
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1answer
397 views

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 ...
1
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0answers
181 views

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 ...
12
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2answers
8k views

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) ...
9
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1answer
3k views

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 ...
6
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1answer
763 views

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 ...