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Questions tagged [performance]

The tag has no usage guidance.

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0answers
15 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
20 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 ...
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1answer
36 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 ...
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0answers
30 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
28 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 ...
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0answers
19 views

Fast Style Transfer memory usage

I'm trying to integrate this tensorflow implementation of fast style transfer with GIMP, the open source image editor. In a few word, the plugin would be a wrapper to the ...
3
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1answer
286 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. ...
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4answers
69 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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4answers
176 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-...
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1answer
40 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 ...
2
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2answers
54 views

Logloss vs Accuracy. Which needs to be chosen to evaluate the model performance

While model tuning using Cross validation and Grid search , I was plotting the graph of different learning rate against logloss and accuracy separately. Graph of Logloss --> learning Rate When I ...
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0answers
45 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
47 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
39 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
75 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 ...
0
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1answer
31 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 ...
0
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1answer
45 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 ...
2
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1answer
114 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 ...
10
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1answer
95 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 ...
0
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1answer
20 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
78 views

Performance Evaluation Metrics used in Training, Validation and Testing [closed]

Which specific performance evaluation metrics are used in training, validation and testing and why? I am thinking error metrics (RMSE, MAE, MSE) are used in validation, and testing should use a wide ...
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2answers
159 views

What makes you confident in your results? At what point do you think you can present your work to tech illiterate superiors?

I understand that the models are only as good as the data you get, and bad design can generate really bad data. Nonrandom sampling, unbalanced/incomplete designs, confounding, can make data analysis ...
2
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1answer
752 views

Interpreting confusion matrix and validation results in convolutional networks

I need some help in the assessment of the training results of a convolutional neural network. Here is my setup: Architecture: InceptionV3 Pre-trained InceptionV3 with weights from image net ...
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0answers
562 views

Transfer learning: Poor performance with last layer replaced

I am using a transfer learning approach. For this I followed the tensorflow for poets tutorial. I use a pre-trained InceptionV3 architecture trained on the Imagenet dataset. The last layer and the ...
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1answer
2k 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
214 views

External GPU vs. internal GPU for machine learning

What are the pros/cons of using external GPUs (e.g., connected through thunderbolt) vs. internal GPUs for machine learning?
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0answers
67 views

Performance Metric for topic extraction when there is no ground truth

I am extracting topics from text using a predefined ontology containing 2690 concepts, wordnet(to expand concept terms with their synsets, and other morphological forms of the same word) and lucene to ...
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0answers
22 views

How to measure the performance of a deep learning model in parasite detection?

I’m working with segmented cells from thin blood smear images and using deep learning models to classify parasitic and uninfected cells. I obtained the following values: Accuracy: 0.986, AUC: 0.99, ...
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1answer
684 views

how should I measure performance if there is no test data?

I have 'practice' data set which I can split into training, validation, and test set and I will play with data to make a machine learning model. But in real situation, I will be given a very small ...
1
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1answer
42 views

How to select a model based on statistical analyses?

I've been statistically validating the performance of different Deep Learning models in classifying parasitized and normal cells. In the process, I could find that there is no statistically ...
6
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2answers
8k 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-...
0
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1answer
374 views

Why use the .idx data format?

The MNIST handwritten digit dataset uses a file format .idx. What are the advantages of this file format over alternatives such as CSV, TSX and ODS?
0
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1answer
31 views

How to evaluate the performance based on rate data

I have the following data: Goal Achieved 100 90 150 130 200 175 ... The first column "Goal" is the number which should be done that ...
0
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2answers
117 views

How do I compare traditional classifiers performance with my proposed method?

I want to compare my proposed method with traditional machine learning classifiers like Multilayer Perceptron(MLP) and SVM to check the classification accuracy.How do I compare different classifiers?. ...
1
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1answer
429 views

How to compare performance of Cosine Similarity and Manhatten Distance?

I'm doing clustering of documents by applying k-Means on the word-vectors. To measure the cluster quality, I calculate David Bouldin Index for different k's. I tried two different distance measures, ...
2
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1answer
2k views

Performance issues when merging two dataframe columns into one on millions rows with Pandas

I am trying to merge two address columns into one and separate the resulting string with '--'. The dataset has 10 million rows and 33 columns - but the number of rows grows for a million or so a month....
1
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2answers
70 views

ML models: average of all versus average of averages?

I have data for 20 different people and am training a model (e.g. a neural network with the same hyperparameters) on the data from each person; so this gives me 20 models. I chose to use RMSE to ...
4
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1answer
116 views

Estimating Titan X graphics card impact on performance

I'm currently training CNNs using Tensorflow (Python) on my GTX 970 (specs here). I recently took a look at the new pascal based Titan Xs and I'm wondering what an estimated performance/speed gain ...
2
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1answer
203 views

Comparing Non-deterministic Binary Classifiers

I have two classifiers which I am implementing, and they are both non-deterministic in the sense that they can each give different results (FPR and TPR) when you run them multiple times. I would like ...
2
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1answer
71 views

Vectorizing/Parallelizing DataFrame indexing

I want to make the following Python data-processing code more efficient by replacing for loops. Is there any way to vectorize code like this? I have a DataFrame object ...
10
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4answers
812 views

How to compare the performance of feature selection methods?

There are several feature selection / variable selection approaches (see for example Guyon & Elisseeff, 2003; Liu et al., 2010): filter methods (e.g., correlation-based, entropy-based, random ...
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2answers
1k views

Using the trainbr function for classification in Matlab

I am training a neural network for classification using Matlab, and I don't understand if I can use the trainbr training function (Bayesian Regularization ...
1
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0answers
43 views

Is there a machine learning framework that supports partial evaluation ie can return a function?

Is there a machine learning framework that supports partial evaluation? For example: We train on [model, year, km, ..., colour, price]. Today we call ...
9
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1answer
7k views

Why doesn't training RNNs use 100% of the GPU?

I wonder why training RNNs typically doesn't use 100% of the GPU. For example, if I run this RNN benchmark on a Maxwell Titan X on Ubuntu 14.04.4 LTS x64, the GPU utilization is below 90%: The ...
1
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1answer
158 views

Optimal parameter estimation for a classifier with multiple parameters

The image on the left shows a standard ROC curve formed by sweeping a single threshold and recording the corresponding True Positive Rate (TPR) and False Positive Rate (FPR). The image on the right ...
1
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2answers
985 views

Benchmarks based on neural networks libraries to compare the performance between different GPUs

I am looking for benchmarks based on neural networks libraries (Theano/TensorFlow/Torch/Caffe/…) to compare the performance between different GPUs. I am aware of: https://github.com/jcjohnson/cnn-...
2
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2answers
140 views

ARIMA(X) Validation

I'm in the process of developing a new spark-based ARIMA(X) tool, and have reached the point where I need to know whether my coefficient estimates and forecasts are sensible. I can compare my results ...
0
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2answers
64 views

What do this Classification evaluation results mean to you? Do they are suspicious or not?

I have collected dataset with two class labels and used the SVM Method to classify the dataset, and this is the results. Does this appear suspicious or not? scikit-learn classifiers with SVM SVC ...
0
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1answer
33 views

Measuring performance of different classifiers without class type in data

To measure the performance of a classification algorithms on a dataset that has an attribute for class type, I divide my dataset to training and test samples and then create a ...
0
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1answer
43 views

Cross-validation strategy

I have a regression problem and I am in doubt about how I can calculate RMSE in my life-cycle. I deal with time-series and for every prediction, I want to look N points in the future. It is apparent ...