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H: MSE to predict Values 0 and 1
I am building a deep neural network to predict values 0 and 1 .My training data contains class labels 0 and 1 .Currently i am getting a cross validation loss around .25 . How good is the model performing?
AI: Predicting $0.5$ for all items in your case would also give you MSE of $0.25$... |
H: Basic method of optimizing hyperparameters
I recently read the LIPO blog post on the dlib blog:
http://blog.dlib.net/2017/12/a-global-optimization-algorithm-worth.html
It mentions that it can be used for optimizing hyperparameters of eg metaheuristic algorithmsike simulated annealing or genetic algorithms.
I looke... |
H: Classify sentences containing typos into groups
My data is a list of sentences, where each sentence contains between 1 and 4 words. These sentences are typed in manually so some of them contain typos and some additional words such as GmbH, GER etc.
However, I do know the set of valid sentences. As an example we ass... |
H: How to treat input that inherently has a tree structure?
When having a single vector you use an MLP neural network
When having a 2D structure you use a CNN neural network
When having a sequence you use a RNN neural network
Now you have preprocessed an instance and the result is a tree structure.
Let's say for simpl... |
H: How would be plotted the logistic functions associated to a multiclass logistic classifier in a X-Y plot?
Logistic function is well known to be a good binary classificator, as it can be easily shown with this image (let x be the dot product of [x1,x2] and [w1, w2]): enter image description here
I am currently lear... |
H: Binary classification toy problem
I'm trying to build a toy model which can identify a constant difference between two variables: (if variable1- variable2>10 then 1 else 0).
This should be a quite simple task for any regression model, but I want to solve it with NN. However all simple NN I built can not give me mo... |
H: unique column value in python numpy
my array is looking like this
a=np.array([[ 25, 29, 19, 93],
[ 27, 59, 23, 345],
[ 24, 426, 15, 593],
[ 24, 87, 50.2, 139],
[ 13, 86, 12.4, 139],
[ 13, 25, 85, 142],
[ 62, 62, 68.2, 182],
[ 27, 25, 20, 150],
... |
H: How can I fit categorical data types for random forest classification?
I need to find the accuracy of a training dataset by applying Random Forest Algorithm. But my the type of my data set are both categorical and numeric. When I tried to fit those data, I get an error.
'Input contains NaN, infinity or a value too... |
H: After a Feature Scaling do i have the same initial information?
I'm studying the gradient descent algorithm for single hidden layer neural networks.
Suppose that I have an initial dataset and then I use mean normalization in order to scale the features.
Why mathematically do the normalized features carry the same i... |
H: Converting similarity matrix before inputting to t-sne
I have a cosine similarity matrix where I want to adjust it to inputto t-sne. I fond the following explanation in a FAQ. As mentioned there I have made the diagonals to zero. what does it mean by symmetrize the pairwise similarity matrix, and normalize it to su... |
H: after grouping to minimum value in pandas, how to display the matching row result entirely along min() value
The dataframe contains
>> df
A B C
A
196512 196512 1325 12.9010511000000
196512 196512 114569 12.9267705000000
196512 196512 118910 12.8983353775637
196512 196512 100... |
H: Ordinal Integer variable vs Continuous Integer variable
I am working on titanic dataset. I have one feature Pclass which I understand is an ordinal variable having values 1,2 and 3. I have created a new feature cabin_int from feature Cabin, which is essentially the number of cabins alloted to a passenger. So, it ha... |
H: Gradient Exchange
I read a paper on Deep Neural Networks Compression (link: https://openreview.net/forum?id=SkhQHMW0W) and came across a term "gradient exchange", I tried making sense out of it but couldn't exactly understand what it intuitively refers to. What does the term gradient exchange mean?
AI: Gradient exc... |
H: How to extract specific parts of text from a string?
For example:
Here is a textual input:
"ALL imagery SINCE 1952
20 MULE T
aerial BOOSTER
& Multi-Purpose Neutralizer.MAY BE “AHMFLL |-E SWALL """""" -5 NETWT4LBS1 DZ (65 OZ) 1.84 kg
"
Output desired:
4 LBS
65 OZ
1.84 kg
"
AI: It is a specific pattern which can ... |
H: Which one of these tasks will benefit the most from SPARK?
My company processes Data (I am only an intern). We primarily use Hadoop. We're starting to deploy spark in production. Currently we have have two jobs, we will choose just one to begin with spark. The tasks are:
The first job does analysis of a large quan... |
H: What is the shape of conv3d and conv3d_transpose?
I want to do a GAN with coloured pictures. This means I need a three dimensional input and therefore I like to use conv3d and conv3d_transpose.
Unfortunately in the TensorFlow documentation, I can't find any formula for the output shape. Can anyone give me a hint on... |
H: Scikit alternative for categorical data modeling?
So, sklearn doesn't support categorical data in its models. Is there a known alternative for categorical data modeling (such as random forests, etc.) for Python?
AI: There are definitely ways to process your data to make categorical data compatible with sklearn (e.g... |
H: Find similar observations in two datasets
I have two datasets A and B. What I would like to do is for each observation in A, I would like to find 5 observations from B that are closest and match to A.
How should I start?
Thank you for your help!
AI: Look at "unsupervised nearest neighbor" algorithm. This algorithm... |
H: Performing machine learning on small datasets
As a beginner at machine learning, I wanted to work on a small project in which the dataset has only 80 rows and 5 columns. The dataset I am working with is related to a medical condition, with 4 columns as biomarkers, and the 5th column indicates whether the row (a pat... |
H: When to use different Word2Vec training approaches?
So I am learning Word2Vec for the first time and my question is quite basic: How to know what approach to use? I.e, Word2Vec in Tensorflow or Word2Vec trained with Gensim ?
In what cases would implementing it through the more manual first approach be useful vs. t... |
H: Can I use cosine similarity as a distance metric in a KNN algorithm
Most discussions of KNN mention Euclidean,Manhattan and Hamming distances, but they dont mention cosine similarity metric. Is there a reason for this?
AI: Short answer: Cosine distance is not the overall best performing distance metric out there
A... |
H: Beginner math books for Machine Learning
I'm a Computer Science engineer with no background in statistics or advanced math.
I'm studying the book Python Machine Learning by Raschka and Mirjalili, but when I tried to understand the math of the Machine Learning, I wasn't able to understand the great book that a frien... |
H: Use cases for graph algorithms and graph data structures in finance and banking
I work in a bank and most data is in tabular format in relational databases. I have been reading about graph algorithms (page rank), graph libraries (spark graphx) and graph databases (neo4j). I would like to pick a use case from my fie... |
H: Is my understanding of On-Policy and Off-Policy TD algorithms correct?
After reading several questions here and browsing some pages on the topic, here is my understanding of the key difference between Q-learning (as an example of off-policy) and SARSA (as an example of on-policy) methods. Please correct me if I am ... |
H: Why is ReLU used as an activation function?
Activation functions are used to introduce non-linearities in the linear output of the type w * x + b in a neural network.
Which I am able to understand intuitively for the activation functions like sigmoid.
I understand the advantages of ReLU, which is avoiding dead neur... |
H: Filter row depending on specific object value and delete those instances
I have some categorical data which also contains '?' as data in some rows. I need to filter those rows depending on '?', that which row contain that instances will be deleted.
I tried to drop those rows by applying these command but I failed... |
H: rows to columns in data.table R (or Python)
This is something I can't achieve with the reshape2 library for R. I have the following data:
zone code literal
1: A 14 bicl
2: B 14 bicl
3: B 24 calso
4: A 51 mara
5: B 51 ... |
H: Big Data - Data Warehouse Solutions?
I have a dozen of databases that stores different data, and each of them are 100TBs in size. All of the data is stored in AWS services such as RDS, Aurora and Dynamo.
Many times I find myself need to perform "joins" across databases, for example a student ID that appears in mult... |
H: Bootstrapping or Randomly Dividing Dataset to reduce variance?
If I have 10,000 training samples then what should I do:
Bootstrapping and train 10 classifiers on it and then aggregating
Or
randomly divide the dataset into 10 parts and train 10 classifiers on them and then aggregating. Which will be better?
Will t... |
H: Is there a maximum limit to the number of features in a Neural Network?
I have created a dataset which has rather large number of features for example-100,000. Is it too large for a decent computer to handle ( I have a 1080ti )?
AI: It highly depends on your data. If it's image, I guess it is somehow logical but if... |
H: How to estimate probabilities of different classes for a Text
Suppose I have a piece of writing and I want to assign probabilities to different genres (classes) based on its contents. For example
Text #1 : Comedy 10%, Drama 50%, Fiction 20%, Romance 1%, Mythology 5%, Adventure 10%
Text #2 : Comedy 40%, Drama 3%, F... |
H: How do I get the name of Sagemaker Estimator's job
I'm having a stumbling block with SageMaker. How do I know what my job name is?
For example:
mnist_estimator = MXNet(entry_point='/home/ec2-user/sample-notebooks/sagemaker-python-sdk/mxnet_mnist/mnist.py',
role=role,
... |
H: Backpropagation with multiple different activation functions
How does back-propagation handle multiple different activation functions?
For example in a neural network of 3 hidden layers, each with a separate activation function such as tanh, sigmoid and ReLU, the derivatives of each of these functions would be diff... |
H: Q Learning Neural network for tic tac toe Input implementation problem
I've recently become interested in machine learning, specifically neural networks, and after creating ones to solve basic problems such as XOR and Sin and Cos graphs, however i am now looking into reinforcement learning and specifically q learni... |
H: TypeError: unsupported operand type(s) for *: 'float' and 'dict_values'
I'm attempting to compute the class_weights for an highly imbalanced set of 9 classes based on the examples discussed in How to set class weights for imbalanced classes in Keras?. Here is the code:
import numpy as np
import math
# labels_dict ... |
H: Should I Impute target values?
I am new to data science and I am currently playing around a bit. Data exploration and preparation is really annoying. Eventhough I use pandas.
I achieved imputing missing values in independant variables. For numerical data by using the Imputer with the means strategy and for one cate... |
H: General Machine Learning Workflow Question
I'm very new to machine learning and want to understand the general process by which it is carried out. I've worked through the famous 'iris' tutorial and want to ask if the principles in that tutorial are applicable to every future machine learning project I undertake.
I ... |
H: Neural network q learning for tic tac toe - how to use the threshold
I am currently programming a q learning neural network tha does not work. I have previously asked a question about inputs and have sorted that out. My current idea to why the program does not work is to do with the threshold value. this is a neura... |
H: Q learning Neural network Tic tac toe - When to train net
This is another question I have on a q learning neural network being used to win tic tac toe, which is that im not sure i understand when to actually back propogate through the network.
What i am currently doing is when the program plays through the game, if... |
H: Neural Network Performs Bad On MNIST
I've been struggling with Neural Networks for a while now.
I get the math behind backpropagation.
Still as reference I'm using the formulas from here.
The Network learns XOR:
Prediction After Training: [0.0003508415406266712] Expected: [0.0]
But basically doesn't learn anythi... |
H: How to define weights on Keras neural network
I have a neural network model written in Keras with (8,5,5,5,32) neurons, as follows:
# Sequential
model = Sequential()
# Neural network
model.add(Dense(5, input_dim=len(X[0]), activation='sigmoid' ))
model.add(Dense(5, activation='sigmoid' ))
model.add(Dense(5, activa... |
H: cosine_similarity returns matrix instead of single value
I am using below code to compute cosine similarity between the 2 vectors. It returns a matrix instead of a single value 0.8660254.
[[ 1. 0.8660254]
[ 0.8660254 1. ]]
from sklearn.metrics.pairwise import cosine_similarity
vec1 = [1,1,0,1,1]
ve... |
H: Can't interpret the text information and ratings matrix imported to NN
I have a Recommender system which uses a Collaborative bayesian approach using pSDAE for recommending scientific articles from the Citeulike Dataset
The text information (as input to pSDAE) is in the file mult.dat and the rating matrix (as input... |
H: What do you pass for the cv parameter in the sklearn method cross_val_score
In sklearn, there is a method for cross validation called cross_val_score. One of the parameters of this method is 'cv'.
I understand in cross validation, there is no splitting the data into training and validation (70-30 split). Instead, y... |
H: How to check for overfitting with SVM and Iris Data?
I am using machine learning predictions for the sample iris dataset. For instance, I am using the support vector machines (SVMs) from scikit-learn in order to predict the accuracy. However, it returns an accuracy of 1.0. Here is the code I am using:
X_train, X_te... |
H: How does k fold cross validation work?
You split the data in k subsamples. Train it on k-1 subsamples, test it on kth subsample, record the performance with some error merric.
Do it k times for each of the k subsamples, record the error each time.
Then choose the model with the lowest error?
Is it the same as ensem... |
H: Isolation Forest height limit absent in SkLearn implementation
In the original publication of the Isolation Forest algorithm, the authors mention a height limit parameter to control the granularity of the algorithm. I did not find that explicit parameter on the Sklearn implementation of the algorithm, and I was won... |
H: Image similarity without perspective
I want to determine the similarity between images based on different features. The images show the same type of object (e.g. cars). I want to order images based on their similarity (e.g. through a feature vector). There are ways to solve this, for example a convolutional neural ... |
H: How to use different classes of words in CountVectorizer()
Suppose I have a piece of writing and I want to assign probabilities to different genres (classes) based on its contents. For example
Text #1 : Comedy 10%, Horror 50%, Romance 1%
Text #2 : Comedy 40%, Horror 3%, Romance 30%
We have given keywords in each ... |
H: Is PCA considered a machine learning algorithm
I've understood that principal component analysis is a dimensionality reduction technique i.e. given 10 input features, it will produce a smaller number of independent features that are orthogonal and linear transformation of original features.
Is PCA by itself conside... |
H: How does KNN handle categorical features
For a K nearest neighbors algorithm using a Euclidean distance metric, how does the algorithm compute euclidean distances when one(or all) of the features are categorical? Or does it just go by the most commonly occurring value among the neighbors?
So e.g. if the 2 features ... |
H: Convolutional Neural networks
Hi all: I have a very fundamental question on how CNN works.
I understand fully the training process as to take a bunch of images, start with random filters, convolve, activate, calculate loss, back propagate and learn weights. Fully understood.
But once the training is done, the last ... |
H: Ways to convert textual data to numerical data
I've been looking for ways to wrangle my data which contains both text and numerical attributes.
There are of course several algorithms for numerical data, but I am looking for suggestions regarding how to deal with textual data, for instance: for sorting based on K-me... |
H: Getting unexpected result while using CountVectorizer()
I am trying to use CountVectorizer() in a loop, But I am getting an unexpected result. On the other hand, if I use it outside the loop then it works fine. I believe there is some small problem with the logic.
from sklearn.feature_extraction.text import CountVe... |
H: Does class_weight solve unbalanced input for Decision Tree?
I've read in sklearn's documentation that we have to take special care in balancing the input for a decision tree, but it doesn't tell you what function to use. However, I've found the parameter class_weight. If I use class_weight: balanced as a parameter,... |
H: CNN - How does backpropagation with weight-sharing work exactly?
Consider a Convolutional Neural Network (CNN) for image classification. In order to detect local features, weight-sharing is used among units in the same convolutional layer.
In such a network, the kernel weights are updated via the backpropagation a... |
H: Choosing an embedding feature dimension
I'm trying to tackle a classification problem with a neural net tensor using flow.
I have some continuous variable features and some categorical features.
The continuous features are normalized using sklearn's StandardScaler.
For the categorical features I am using a series ... |
H: Clustering for multiple variable
There are total 50 students(john, Roy..) and used some action to do a job. My dataSet something like this
John Roy Micheal Ron ....... Smith
A B B A C
A A C B B
C A A B ... |
H: Format for time series data with non-trivial sampled data
I have a data stream that I would like to share with some data scientists.
It is a regularly captured time series with some fields that are simple scalars, booleans. Each sample has a UTC time and fractional seconds since start of capture.
Also captured is... |
H: Link prediction with input data
I have a list of files, an I use the KNN algorithm to classify these files.
dataset = pd.read_csv(file)
training_samples = get_sample_number(dataset)
X_train = dataset.iloc[:training_samples, 5:9]
y_train = dataset.iloc[:training_samples, 9]
X_test = dataset.iloc[training_samples:, 5... |
H: Naïve Bayes and Training Data
I am creating my own implementation of a Naïve Bayes classifier. While it’s behaviour and functionalities are clear to me, my concerns are on the nature of the training and testing data.
I acquired several sets of product reviews from Amazon. The first thing I do is parsing them, that ... |
H: Should I prevent augmented data to leak to the test/cross validation sets
I have been working with the cats vs dogs dataset from kaggle which consist on 25000 images of cats and dogs labelled accordingly (btw, great dataset, totally recommended!)
One of the things I did was to augment the data by simply fliping the... |
H: High-level features of a neural network
I understand how to build and train a neural network like shown below, as well as those low-level features/filters. I wonder what are those high-level features: how exactly do you obtain them from a trained neural network? (Are those like the "eigenfaces"?)
Note: the image i... |
H: How do you avoid 'analysis paralysis' when choosing a method to implement?
When you have multiple methods to accomplish a task, how do you choose which one to implement?
AI: This is a very broad question but in general you can define some criteria that you want the method to meet (eg low error, efficiency, scalabil... |
H: Keras - Computing cosine similarity matrix of two 3D tensors
Using TF backend, I need to construct a similarity matrices of two 3D vectors, both with shape (batch_size, N, M), being N and M natural numbers.
The function tf.losses.cosine_distance is only between 1D tensors. I need to build a Tensor matrix batch_siz... |
H: What are useful evaluation metrics used in machine learning
I am using CNN in order to predict codes after analyzing text. As an example, I will write "I am crazy" .. the model will predict some code " X321".
All this based on CNN.
I want to evaluate my model. I used Fscore (recall and precision). Can you advice ... |
H: CNN'S are what?
I have a very fundamental question on what CNN'S actually are.
I understand fully the training process as to take a bunch of images, start with random filters, convolve, activate, calculate loss, back propagate and learn weights. Fully understood....
But recently I came across this line on Slack
CNN... |
H: What loss function should I use if I have been working on a classification problem which involves both multi-label and multi-class labels?
For example I have apple and pear pictures. What I am trying to do is to predict if a picture is an apple or pear picture and AT THE SAME TIME predicting whether the fruit is bi... |
H: Can someone spot anything wrong with my LSTM forex model?
The model below reads in data from a csv file (date, open, high, low, close, volume), arranges the data and then builds a LSTM model trying to predict next day's close based on a number of previous days close values.
However, validation accuracy is about 53.... |
H: Hidden Markov Model on R Studio
Is there any detailed materials that can help explain how to set up HMM on R Studio?
AI: You can take a look at here. As you can read from there:
Download and unpack hiddenDomains
If you haven't already done this, download the latest version of hiddenDomains from the Sourceforge w... |
H: LSTM Implementation using tensorflow (anaconda)
I'm new to TensorFlow and currently I'm trying to implement an LSTM using jupyter notebook.
But when I run the following code segment, I got some errors and couldn't find any solution.
How can I work through this error?
Code:
lstmCell = tf.contrib.rnn.BasicLSTMCell(ls... |
H: To be useful, doesn't a test set often become a second dev set?
I'm a little unclear about the expected use/value of a test set in machine learning. Here is a story that explains my confusion, assuming you're using a train/dev/test split:
You use your dev set to choose the best hyperparameters and make various twea... |
H: Are linear regression models with non linear basis functions used in practice?
I know that popular linear regression models such as Lasso or Logistic Regression are widely used in practice because they perform reasonably good, are efficient and interpretable.
As far as I know, the only way for these models to lear... |
H: How exactly does matrix factorization help with collaborative filtering
We start with a matrix of user ratings for different movies with some elements unknow i.e the rating of a yet to be seen movie by an user. We need to fill in this gap. So
How can you decompose or factorize a matrix where all elements are not ... |
H: Is there a package for using SQL to manipulate Pandas dataframes in Python?
Rather than learn a new package/language, I'd like to use my existing SQL skills to manipulate pandas dataframes in Python. Does anyone know of a way to do this, or perhaps a package that will allow me to do this?
AI: I found a package call... |
H: Compute backpropagation
I have the question which is mentioned in the above picture. It is trying to find the derivative of f with respect to weight matrix W1. Can any one help me how I can accomplish that?
I solved in this way :
AI: You are missing one little step here. At the output node the backpropagation algo... |
H: Gradient Descent in logistic regression
Logistic and Linear Regression have different cost functions. But I don't get how the gradient descent in logistic regression is the same as Linear Regression.
We get the Gradient Descent formula by deriving the Squared Error cost function. However in Logistic Regression we ... |
H: Reducing text input size into word2vec without affecting performance too badly?
So I am implementing Word2Vec for the first time, and I have a set of training data that I would like to train a word2vec model on. Predictably, the problem is the dataset is rather large, and I have more limited computational power tha... |
H: What exactly is bootstrapping in reinforcement learning?
Apparently, in reinforcement learning, temporal-difference (TD) method is a bootstrapping method. On the other hand, Monte Carlo methods are not bootstrapping methods.
What exactly is bootstrapping in RL? What is a bootstrapping method in RL?
AI: Bootstrappi... |
H: "concat" mode can only merge layers with matching output shapes except for the concat axis
I have a function I am trying to debug which is yielding the following error message:
ValueError: "concat" mode can only merge layers with matching output
shapes except for the concat axis. Layer shapes: [(None, 128, 80,
... |
H: validation_curve differs from cross_val_score?
I'm trying to see how well a decision tree classifier performs on my input. For this I'm trying to use the validation and learning curves and SKLearn's cross-validation methods. However, they differ, and I don't know what to make of it.
The validation curve shows up as... |
H: Should the output of regression models, like SVR, be normalized?
I have a regression problem which I solved using SVR. Accidentally, I normalized my output along with the inputs by removing the mean and dividing by standard deviation from each feature.
Surprisingly, the Rsquare score increased by 10%.
How can one e... |
H: Why won't my SVM learn a sequence of repeated elements
I recently started playing with SVMs for a one class classification, I was able to get some reasonable classifications from real data and but was trying to optimize the nu and gamma parameters when I came across this example:
In the code below, I train an SVM w... |
H: Understanding of naive bayes: computing the conditional probabilities
For a task on sentiment analysis, suppose we have some classes represented by $c$ and features $i$.
We can represent the conditional probability of each class as: $$P(c | w_i) = \frac{P(w_i|c) \cdot P(c)}{P(w_i)}$$
where $w_i$ represents each fe... |
H: Cleaning input data with pd.get_dummies()
What is the advantage of converting a series like
>>> df
Color
0 Red
1 Blue
2 Green
3 Red
To a multiple series like the below?
>>> pd.get_dummies(df)
Color_Blue Color_Green Color_Red
0 0 0 1
1 1 0 ... |
H: How to understand incremental stochastic gradient algorithm and its implementation in logistic regression [updated]?
I have a difficulty where to start the implementation of incremental stochastic gradient descent algorithm and its respective implementation in logistic regression. I don't quite understand this algo... |
H: How to get spike values from a value sequence?
I have pile of vectors where the values could be plotted like this:
Now I want to extract the "spike values" (over a certain threshold say 15,000). In this case there is fifteen. How could this be done with Python? (There is no predefined number of spikes but the thre... |
H: GloVe vector representation homomorphism question
In the paper GloVe: Global Vectors for Word Representation, there is this part (bottom of third page) I don't understand:
I understand what groups and homomorphisms are. What I don't understand is what requiring $ F $ to be a homomorphism between $ (\mathbb{R},+) $... |
H: Autoencoder for anomaly detection from feature vectors
I am trying to use an autoencoder (as described here https://blog.keras.io/building-autoencoders-in-keras.html#) for anomaly detection. I am using a ~1700 feature vector (rather than images, which were used in the example) with each vector describing a differen... |
H: Shape classification algorithm
I have a dataset of shape edges, that I am trying to make a model for with sklearn. I'm new to the machine learning world, so I am struggling to create a good model. Using SVM, I was able to get a supposed 81% precision, but when I feed it an image outside the training or test set, it... |
H: How to validate different method of clustering
I have applied K-means and Hierarchical Agglomerative clustering method on some data and clustered them into 5 groups. For validation (agreement) purpose I used this formula:
c=(# of cluster shared/ Total cluster)*100 %
I feel its a wrong validation technique.
Can I u... |
H: ValueError while using linear regression
I have loaded a dataset and converted into data frame while I am using linear regression I am receiving the following value error as shown in my code below. I am at the moment doing a tutorial and could not figure out how come the arrays are 1-D as the error shows.
from skle... |
H: What algorithm can predict structured outputs of arbitrary size?
I have a collection of graph objects of variable size (input) which are each paired to another graph of variable size (output). The task is, given an input graph, produce the most likely output graph.
I have been looking at 'structured output' techni... |
H: Softmax: Different output scikit-learn and TensorFlow
I'm trying to learn a simple linear softmax model on some data. The LogisticRegression in scikit-learn seems to work fine, and now I am trying to port the code to TensorFlow, but I'm not getting the same performance, but quite a bit worse. I understand that the ... |
H: How to cross-validate a deep learning model for highly imbalanced datasets?
I am working with a multi-modality classification problem (with Keras). I have 1000, 5000 and 10000 samples for three different classes. I would like to do a five fold cross-validation to select the best pre-trained deep learning model for ... |
H: What are some methodologies for performing feature selection for simple feed-forward neural networks?
In multiple linear regression there is an F-test which can be used to evaluate whether or not a covariate has a meaningful impact on a model. This is typically done through either a forward selection or backwards s... |
H: Preparing custom dataset for object detection using ML
Seeking clarity on single class object detection model using ML. I have prepared a custom database for this purpose up to 400 images which is split in 80%-20% as training and testing data-set. These are top view only images. The data collection followed the bas... |
H: What do mean and variance mean for high dimensional data?
I'm using Scikit Learn to guess the tag of Stack Overflow posts given the title and body. I represent the title and body as two 300-dimensional vectors of floats. The documentation for Scikit learn's SGDClassifier states:
For best results using the default ... |
H: Decision Tree used for Calculating Precision, Accuracy, and Recall, class breakdown question
I am creating decision trees modeling data that looks like this.
pelvic_radius degree_spondylolisthesis class
82.45603817 41.6854736 Abnormal
114.365845 -0.421010392 Normal
When finished, I run m... |
H: How to correctly resize input images in a CNN?
I have a training set composed of images having different width and height, I need to resize them to a fix dimension nxn or nxm before passing them as the input of a CNN.
I would like to know which parameters I need to take into account for correctly choose the new sca... |
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