Questions tagged [performance]

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1answer
27 views

Difference Between Performance Scores

I need some help to understand the meaning between these different scores. Currently, I am doing the classification problems using machine learning, and I have obtained the results for the ...
10
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4answers
373 views

Performance measure: Why is it called recall?

precision is the fraction of retrieved instances that are relevant, while recall (also known as sensitivity) is the fraction of relevant instances that are retrieved. I know their meaning but I don'...
5
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4answers
780 views

Log loss vs accuracy for deciding between different learning rates?

While model tuning using cross validation and grid search I was plotting the graph of different learning rate against log loss and accuracy separately. Log loss When I used log loss as score in ...
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2answers
69 views

AUC ROC Threshold Setting in heavy imbalance

I am doing binary logistic regression on a dataset with very heavy class imbalance. Class 1 is only 1% of data. When I train logistic regressor without class weights I get ROC AUC Score of 0.6269. ...
5
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1answer
217 views

Why ML model produces different results despite random_state defined? And how to set global random seed for sklearn

I have been running few ML models on same set of data for a binary classification problem with class proportion of 33:67. I had the same algorithms and same set of hyperparamters during yesterday and ...
2
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3answers
66 views

Is over-fitting a matter of features engineering or a matter of parameters set?

I am using sklearn package to make models. I tried randomly to set some paramater to a sklearn.ensemble.RandomForestClassifier ...
2
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1answer
31 views

Relating ROC curves with class statistics

I have three neural net models that I am running on the same dataset (of 7 classes) and calculate their class performance and also ROC curves. The firs tmodel is a 4-layer model with 8 neurons in each ...
1
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1answer
127 views

How to decide optimal threshold for my classification model from FPR, TPR and threshold

I am building my model in Python to classify customer in buyer/ non-buyer category. I used mutiple agorithms for this problem and then after evaluation selecting the best out of all. sklearn package ...
1
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1answer
248 views

bad regression performance on imbalanced dataset

My current dataset has a shape of 5300 rows by 160 columns with a numeric target variable range=[641, 3001]. That’s no big dataset, but should in general be enough for decent regression quality. The ...
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1answer
24 views

Customer Intelligence - How to measure success?

we are creating models that aim to filter new leads from our current customer base. We started to create propensity models that calculate a percentage for each customer for a certain product group. I ...
3
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2answers
28 views

Does Sampling size matters in Multi classification Model

I am working on a multi class classification model where few of the class are with less data compare to other classes. I used random sampling technique to create a sample from the population keeping ...
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0answers
18 views

How to improve computation speed on Orange?

I need to process huge data sets on Orange 3.23. My Orange workflow contains several widgets in parallel. It seems that Orange launches each process at a time. Is there a way to run several processes ...
1
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1answer
25 views

How can we conclude that an optimization algorithm is better than another one

When we test a new optimization algorithm, what the process that we need to do?For example, do we need to run the algorithm several times, and pick a best performance,i.e., in terms of accuracy, f1 ...
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1answer
155 views

why does performance of machine learning models plateau after certain amount of training data

I'm referring to the below image which I came across. The explanation seemed intuitive at first but I don't think I understand how it works. The image says that the performance of traditional machine ...
9
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3answers
13k views

Improve Pandas dataframe filtering speed

I have a dataset with 19 columns and about 250k rows. I have worked with bigger datasets, but this time, Pandas decided to play with my nerves. I tried to split the original dataset into 3 sub-...
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0answers
48 views

Doc2vec doesn't use all the CPU power

I have a big dataset that trying to train with a Doc2vec model. I am working on a 8 CPU, 32GB RAM, but as I can see on the monitoring tools, it only uses about 66-67% of the CPU. I am not sure if it ...
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2answers
248 views

How can I perform backpropagation directly in matrix form?

I had made a neural network library a few months ago, and I wasn't too familiar with matrices. So, instead of performing matrix dot products (between weights and inputs, then adding a bias matrix), I ...
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0answers
12 views

Evaluating randomness in a model performance

I'm evaluating the variability in performance (AUC) in the test set of a machine learning model with an intrinsic random component (xgboost). How many sources of variation should I use? Just ...
2
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1answer
77 views

Xgboost multiple class predictive performance beats one versus rest

I have an NLP task I'm tackling with xgboost (R implementation). Before describing my doubt I'll give you some background: I have a corpus of documents for which I did topic discovery, using a term ...
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2answers
51 views

How can i test the performance of a model when the test data contains seen and unseen data

To test the performance of my model based on some selected features, i try to use unseen and seen data. However, when choosing the accuracy based on all data, the model is almost overfitting since ...
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2answers
3k views

Improve Precision of a binary classifier - Decision Tree in Python

Currently, I am working on a project. The dataset is balanced roughly in the ratio of 50:50. I created a decision tree classifier. I am achieving decent accuracy (~75%) on validation data but the ...
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0answers
197 views

How much text is enough to train a good embedding model?

I need to train a word2vec embedding model on Wikipedia articles using Gensim. Eventually, I will use the entire Wikipedia for that but for the moment, I'm doing some experimentation/optimization to ...
1
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1answer
42 views

fast ML algorithms for binary classification with (large+sparse) binary input data

I'm sorry that this is so very broad, but as a non-ML scientist it feels to be almost impossible to keep up with recent developments (esp. in deep learning etc.). Hence, I'm asking for guidance on how ...
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0answers
10 views

Performant alternatives to Matrix package in R that requires minimal effort by end users to install

Background I'm going to be releasing a package for R that does calculations involving extremely large sparse matrices (1,000,000 x 1,000,000 is the minimum for what we consider useful). For this ...
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1answer
18 views

Reordering feature and its impact

How does reordering the features impact model training and its performance? Per my understanding, it should not impact the model performance as weights get tuned according to feature value and not ...
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0answers
66 views

For a multiclass classification problem, how do we find the cohen kappa score?

So I have a multiclass classification problem and I have found the Matthews Correlation Coefficient of that (https://scikit-learn.org/stable/modules/model_evaluation.html#matthews-correlation-...
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1answer
92 views

Normalized metric for comparing regression models performance

I was recently trying to explain to someone whether performance of my estimation approach is good or bad. For instance, whether a model with Mean Absolute Error (MAE) of 17000 is a bad solution. It ...
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0answers
25 views

Changing the performance metric used to optimize with random-forest

I'm looking to change the performance metric used to optimize the training for my data set because it is highly unbalance. Because it's highly unbalanced, I don't feel like accuracy is the appropriate ...
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1answer
149 views

Accuracy improving but, val_acc oscillating in ConvNet. What does it mean?

In my ConvNet model, i'm trying to classify some images. It is malware images and it doesn't contain complex features (i think), as expected model learn to classify images easily. You can see my ...
5
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1answer
240 views

GPU performance is about 50% slower than benchmarks

Running this benchmark I get 50% slower performance than the author on practically all deep learning sub problems (SINGLE precision and on TRAINING only): I tested this on a GeForce 1080 GTX Ti and ...
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0answers
170 views

How to evaluate reinforcement learning model?

I am relatively new to reinforcement learning and have been experiencing with a reinforcement learning model to make decisions based on human activities (dynamic environment). Appreciate if someone ...
0
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3answers
38 views

classification performance metric for high risk medical decisions

What is the best classification performance metric for risky medical treatments like surgery? for example a patient should NOT suggest a surgery (negative) if he/she can be treated by medicine (...
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0answers
44 views

Model Performance using Precision as evaluation metric

I am dealing with an imbalanced class with the following distribution : (Total dataset size : 10763 X 20) 0 : 91% 1 : 9% To build model on this dataset having class imbalance, I have compared ...
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0answers
203 views

How can I calculate perplexity for a bigram model?

I didn't find any function in nltk to calculate the perplexity. There are some codes I found: ...
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0answers
46 views

Cross-validation and out-of-bag bootstrap applications

I have a question regarding steps on which a specific resample method should be used in general. As far as I know: out-of-bag bootstrap is the resample method with replacement, which has lower ...
4
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1answer
212 views

CNN computing time on good CPU vs cheap GPU

I am a researcher working on my first deep learning project, which consists of using a CNN (pre-trained VGG16+2 densely connected layers) to classify drone imagery of vegetation. In trying to hack ...
2
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0answers
141 views

How to choose best model checkpoint when training deep learning model on all the data?

When training a final model for production, it's often recommended to train on all available data (train + dev + test), as discussed here. I'm training a deep learning model. I typically save and use ...
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1answer
31 views

How reliable are model performance reportings?

I had a conceptual doubt about estimating and reporting a classification model's performance. Say my model works with range of depth values and gives out different readings of test errors. We choose ...
25
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4answers
13k views

Is there a straightforward way to run pandas.DataFrame.isin in parallel?

I have a modeling and scoring program that makes heavy use of the DataFrame.isin function of pandas, searching through lists of facebook "like" records of ...
3
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1answer
2k views

AUC ROC in keras is different when using tensorflow or scikit functions.

Two solutions for using AUC-ROC to train keras models, proposed here worked for me. But using tensorflow or scikit rocauc functions I get different results. ...
2
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4answers
222 views

Neural Network unseen data performance

I started dabbling in neural networks quite recently and encountered a situation which is quite strange (at least with my limited knowledge). The problem I'm using a NN is a regression problem which ...
3
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2answers
14k views

What does RMSE points about performance of a model in machine learning?

I am working on Decision Tree algorithm and at the end I calculate RMSE value based on actual labels and predicted values (for ...
3
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4answers
560 views

Metrics to determine K in K-cross fold validation

Consider a scenario where the dataset in hand is quite large, let's assume 50000 samples (quite well balanced between two classes). What metrics can be used to decide the K value in a K-fold cross-...
2
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1answer
51 views

“Each agent was evaluated every 250,000 training frames for 135,000 validation frames” What does this sentences stands for? in DQN nature paper?

In nature paper of DQN by DeepMind, DQN is compared to linear function but they does not said what is this linear function? They compared with some linear functions? 0- What is the meaning of this ...
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1answer
76 views

Regression model performance with noisy dependent variable

I'm doing a support vector regression with the dependent variable representing measurements from an uncalibrated sensor (measurement error between 2% and 20%) and I want to study the effect of this ...
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0answers
73 views

Time-series clustering Quality Measures

I am clustering time-series datasets which are not labeled (No Ground truth) and I want to measure the quality of the clusters. Could you please suggest any Clustering performance evaluation methods ...
2
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1answer
277 views

how to improve searching index in dataframe

Given a pandas dataframe with a timestamp index, sorted. I have a label and I need to find the closest index to that label. Also, I need to find a smaller timestamp, so the search should be computed ...
0
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1answer
47 views

Confidence of this particual prediction

I am looking for a confidence of model to predict well in a given situation. So I have a model $f$ (generic, let's exemplify with a regression model of explicit form for brevity). It well fits on the ...
10
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1answer
739 views

What is the best performance metric used in balancing dataset using SMOTE technique

I used smote technique to oversample my dataset and now I have a balanced dataset. The problem I faced is that the performance metrics; precision, recall, f1 measure, accuracy in the imbalanced ...
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12answers
13k views

How big is big data?

Lots of people use the term big data in a rather commercial way, as a means of indicating that large datasets are involved in the computation, and therefore potential solutions must have good ...