Questions tagged [h2o]

H2O is an in-memory platform for distributed, scalable machine learning.

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21 views

variable importance -frequency and variable importance -cover (h2o)

For some models h2o can produce three forms of variable importance Analysis ( variable importance , variable importance -frequency and variable importance -cover) , can anyone point me to a reference ...
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1answer
37 views

Inconsistency between poisson and negativebinomial in glm

I am working with the negativebinomial distribution for GLM. I have done one test which is finding the poisson distribution results. Here is the first test: ...
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0answers
88 views

Improving Average F1 Score for Multiclass Classification

I'm trying to do a multiclass classification with h2o in R. I stacked a model with a RF, GBM and deeplearning. The accuracy is ok (~0.81), but the average F1 score is bad because class B has a very ...
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3answers
71 views

LASSO or random forest (RF) to use for variable selection when having highly correlated features in a relatively small dataset with many features?

I have a cross sectional data-set with around 1000 features and 5000 observations. There are many features (no categorical features) which are highly correlated (higher than 0.85). I want to decrease ...
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1answer
66 views

h2o glm tweedie for categorical variables

To build a tweedie glm for categorical variables, the document suggested that I can use data['variable_name'].asfactor(). However, in the model output, there is no reference level, i.e., if I have ...
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1answer
27 views

How does H2o handles missing values in DRF? [closed]

Just wanted to confirm that the h2o's implementation of RF (DRF) handles the missing values for both categorical and numerical features the same i.e., as a separate category?
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1answer
41 views

Why are AUC and logloss metrics not available in the “maximum metrics” table produced by H2O? [closed]

I am running the h2o.gbm algorithm using five-fold cross validation to predict a binary outcome. I want to see what threshold to use as a cutoff for classifying predictions, and I am wondering why the ...
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1answer
136 views

How are the training and cross-validation metrics calculated in H2O?

I am working with the GBM algorithm in H2O in R. I am using 100% of the data as the training data, and then using 5-fold cross-validation to train and validate my model using 100% of the data. My ...
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1answer
65 views

How to get prediction interval from a model obtained in h2o?

From an AutoML Leaderboard on H2O, I selected a Stacked Ensemble model. I used this model to predict, using a new data set, and now I would like to obtain prediction intervals in addition to point ...
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0answers
194 views

Feature selection in xgboost vs GBM in H2O

I am working on a big data set( more than 100 variables) and 30 million observations. I tried to build 100 models with a grid search using both XGBoost and GBM in H2O (Sparkling Water). I realized ...
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1answer
400 views

New factor levels in testing data set not present in training data in h20.randomforest

In randomforest classification using h20 package, there are factor levels which are present in testing data but not in training data.There is a warning message in predicting the values of testing data,...
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1answer
40 views

binomial responses in h2o gbm

I am modeling the probability of success in a dataset where I have a both the number of trials and the number of successes (and, obviously, I am modeling $p_i=\frac{total successes}{total trials}$). I ...
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1answer
48 views

What kind of impact do autoencoders have on final model performance when compared to models trained only on supervised data? [closed]

For example, say we have two datasets, a labeled set (I will call it df_labeled) of nrows=200k and an unlabeled dataset (df_unlabeled) of nrows=800k and we want to build a binary classifier. I clearly,...
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1answer
72 views

Quadratic Weighted Kappa metric in H2O package for model performance

I am running a multiclassification problem and before I make a function by myself I was wondering if anyone knows of a pre built quadratic weighted kappa function in the h2o library.
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0answers
31 views

H2O (open source) for K-mean clustering [closed]

I am using H2O (H2O flow, in particular) to do K-means clustering. I selected "standardize" checkbox which makes sure "It standardize columns before computing distances". It trained fine and I ...
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1answer
71 views

H2o k-fold validation [closed]

I need to get some clarification on how H2o creates a training model from the k-fold validations. Below is my understanding, please correct where I am wrong: If I set nfolds = 5, then H2o will split ...
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1answer
97 views

DeepLearning & Anomaly Detection - Understanding & How to Properly Tune

I'm looking into understanding the Deeplearning anomaly detection algorithm provided by h2o. I tried to recreate an example below. Perhaps some of these questions are basic, but I'm trying to better ...
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1answer
263 views

H2O GBM and Caret GBM

Hi I have doubt regarding the interaction. depth parameter in caret. I found a useful link hereabout interaction.depth in caret Now I am trying to find the similar parameter in H2O-GBM . Can anyone ...
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1answer
372 views

categorical_encoding in h2o - what is the difference between the options

I'm trying to understand the pros/cons and when to use the various encoding options that are available to me in h2o with the parameter 'categorical_encoding'. It would be helpful if people could ...
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2answers
273 views

May somebody help with interpretation of trees from h2o.gbm, see as photo attached

This picture is from h2o.gbm, while I'm not sure how to interpret the numbers in it. What is the big title "Class NO" mean? Does it mean the root node is labeled "No"? Or does it mean this tree is ...
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1answer
143 views

Issues with XGBoost on H2O environment

I have a dataset from which I built lags at different levels to use as features in the XGBoost model. When I ran XGBoost models on H2O, the model is picking up the features which contain higher values ...
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1answer
54 views

Is setting a self learning system possible via incremental (online) learning?

Self learning and incremental learning are all new to me. I am trying to develop a system for one of my case. Simply I have a data set (with about 90K observations and 400 features) for a binary ...
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2answers
57 views

How NULLs in numerical variables are treated in tree-based models?

I understand that in tree-based models (CART, Gradient boosted trees, etc.), NULLs (i.e., NaN) in categorical variables can be treated as a separated category, while making node splits. However, how ...
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2answers
45 views

h2o : Any components not running or stored on local machine? [closed]

The descriptive language used when referencing how h2o works is a little confusing to me at times (e.g., client, cluster, "internet"). I try to remain vigilant in not uploading or exposing my datasets ...
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1answer
53 views

Help about cosine simulating in h2o [closed]

So I'm beginning in deep learning and especially in h2o. I tried to simulate cosine function in R, not to compute it like for example by using h2o.cos(), But after many and many more combinations of ...
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0answers
146 views

balance_classes in H2O, but for regression? [closed]

I am training with deep learning for regression in H2O for R. My dataset is unbalanced (ie. not evenly distributed). There has been discussion on whether unbalanced datasets are an issue or not, with ...
4
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1answer
59 views

Special values in continuous numerical variables/features in Random Forest

I have a binary response variable I am seeking to predict using Random Forest. I have a sizable dataset of 150k rows, I have about 200 independent variables or features to use to model the outcome. ...
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1answer
358 views

Extracting H2o Cross Validation Results

I am using H2o library in R and have a slight confusion that you learned people might be able to help with. I am not sure how to interpret the output from ...
1
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1answer
205 views

H2O PCA number of components

I wonder why number of components in H2o PCA algorithm is limited to 9. It is not sure sometimes to be enough. k: Specify the rank of matrix approximation. This can be a value from 1 to 9 and ...
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0answers
211 views

How to improve GBM performance

I'm trying to model insurance losses, with a Tweedie distribution. I have a data set of about 40 million records, and over 100 independent variables. My response variable is "loss", I take the log of ...
2
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1answer
613 views

H2o interpretability - LIME

I have trained a model to predict heart attacks using random forest algorithm using H2O. I have good performance in cross validation. Now, I want to give more interpretation to the predictions in a ...
2
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1answer
172 views

How is deviance defined in H2O Deep Learning if the loss function is not quadratic?

One can set the parameter “stopping_metric” to “deviance” for the deeplearning algorithm (http://docs.h2o.ai/h2o/latest-stable/h2o-py/docs/modeling.html#h2o.estimators.deeplearning....
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46 views

How is the parameter „huber_alpha“ defined in H2O Deep Learning?

In the documentation of the H2O software (http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/deep-learning.html) it says for the parameter “huber_alpha: Specify the desired quantile for Huber/...
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1answer
2k views

H2O AUTOML: How to save, reuse and build on top of existing automl models? [closed]

I have two questions on h2o.automl and I couldn’t find any documentation on these topics. I can save/reuse the leader (automl) model in R using h2o.saveModel and h2o.loadModel. But how do I save/...
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1answer
273 views

feature engineering for auto encoder anomaly detection

I am working on an unsupervised problem: to take a set of transactional data, and identify anomalous transactions. I am using h2o's auto encoder to train a model which then scores transactions based ...
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0answers
70 views

“beta_given” column in the h2o.glm beta_constraints

What does the "beta_given" column do in the h2o.glm beta_constraints parameter? h2o is an open source library for machine learning algorithms. There are several online examples on how to install the ...
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1answer
34 views

Difference in parameters between grid summary and individual models

I was using h2o for getting a feel of what learning rate does a good job on my data set. I chose to use cross validation for selecting a learning rate. ...
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0answers
1k views

Implementing “Balanced Random Forest” in h2o

Currently having problems with (very) imbalanced classes in a dataset that I am trying to run binary classification on. Looking at this UC Berkeley article (http://statistics.berkeley.edu/sites/...
1
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1answer
224 views

Reduce over-forecasting in H2O regression with tree-based algorithms

I'm trying to solve a time series forecasting problem. While accuracy is fine, I'm now trying to punish / reduce under-forecasting events where the forecast is too low. Forecasting approach: Build ...
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1answer
1k views

Training threshold vs validation threshold for better prediction results?

Between the two, should I use a model's training or validation threshold to get best results (from a distributed random forest binary classifier built using h2o.ai) ...
4
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2answers
346 views

Deviances in H2O

does anyone know how exactly the Deviances (Poisson, Gamma, Tweedie) are computed in H2O? I cannot find the functions. For interpretation purposes I would like to know the calculations. Thank you!
4
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1answer
736 views

Regularized GLM with aggregated data

I am fitting a poisson GLM to model claim rates. Since I have 1.5m+ records, I have aggregated my data (to improve efficiency). My understanding is that using aggregated data with a poisson GLM will ...
0
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1answer
221 views

Which algorithm is used for the H2O AutoML metalearner [closed]

We know that h2o.automl() uses GBMs, Random Forest, DNNs, GLMs, and Extremely-Randomized Forest as base-learners, but what algorithm is used as the metalearner to ...
1
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1answer
890 views

Can we force monotonicity for a subset of features in h2o gbms?

I was wondering if it's possible to force variables to be monotonic when building gbms in h2o? Ideally this would be enforced globally, although even the standard local constraint would be better than ...
2
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1answer
296 views

Is polynomial regression possible in H2O? [closed]

Is there a way to carry out polynomial regression $x + x^2$ in H2O (Python)? What I have found about this is "interactions" option in GLM. However, I am not sure if this option yields polynomial ...
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2answers
665 views

can I use h2o or mxnet to do time series prediction?

I have a time series like 4, 6, 10, 12, 2, 23, 4,... It is not a stationary time series so I do not want to use arima algorithm. I perfer neural networks. There is some algorithm in R package such as ...
2
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1answer
599 views

Random Forest cross-validation r2 is high but predictions on simulated data are bad

I have a dataset with 46 million observations and 25 predictors. I am training my model in the python h2o package like so: ...
2
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2answers
447 views

How are the epochs and iterations defined in a h2o deep learning perspective?

As per the usual definition of epoch and iteration, it takes multiple iterations to complete 1 epoch (for example see https://stackoverflow.com/questions/4752626/epoch-vs-iteration-when-training-...
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1answer
347 views

Use of previously set cross validation set for ensemble models in h2o

I have time series dataset and as a requirement I prepare a 10 fold cross validation dataset. Briefly, I split data into 10 and for each training set I put a gap between last, first day of validation ...
4
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2answers
2k views

Random forest variable importance in h2o (classification problem)

I cannot find out how the variable importance for classification problems is calculated in h2o. There is a Stackoverflow question asking the same, but the accepted ...