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H: Can I install Tensorflow in Anaconda without using Keras?
Can I install Tensorflow in Anaconda without using Keras?
If I can what is the difference between using Keras with Tensorflow and only Tensorflow?
AI: Can I install Tensorflow in Anaconda without using Keras?
Absolutely.
If I can what is the difference bet... |
H: Which parameters are hyper parameters in a linear regression?
Can the number of features used in a linear regression be regarded as a hyperparameter? Perhaps the choice of features?
AI: I like the way Wikipedia generally defines it:
In machine learning, a hyperparameter is a parameter whose value is
set before t... |
H: Which machine learning model should I learn for this problem?
I'm working in python. Would like to practice some machine learning, and I've always been curious about an analog to the problem below...
A collection of 3 letters are drawn randomly from the 26 letters of the alphabet. None, any, or all of the letters c... |
H: How to determine the number of forward and backward passes in deep learning (CNN)?
Is there a way to determine the number of forward and backward passes in the training of a neural network using python?
AI: Forward and backward passes of the whole dataset are called epochs. The number of epochs is a parameter of th... |
H: problems during training a MLP type of network
I trained a neural network model, a MLP type of network, where the first several layers are 1-D convolution for processing sequence type of input.
However, the training process looks like as follows, where the orange line represents the validation loss and the blue lin... |
H: Should one hot vectors be scaled with numerical attributes
In the case of having a combination of categorical and numerical Attributes, I usually convert the categorical attributes to one hot vectors. My question is do I leave those vectors as is and scale the numerical attributes through standardization/normalizat... |
H: Using packages such as sklearn vs building ML algorithm from scratch
I have been using different machine learning algorithms throughout various projects at university, and attended some inspirational lectures where industrial companies show and present how they use machine learning, data mining, etc. in their work.... |
H: Why can't I choose my hyper-parameter in the training set?
Say I've divided the data into 3 parts: training, validation and test. I know for example, that in Neural Networks, the number of hidden layers is a hyper parameter. Why can't I train numerous NN architectures in the training set and then test their accurac... |
H: do the results change if you remove duplicate rows and you sum their weights?
Assuming that we have a dataset with the respondents on each row (N respondents) and their respective characteristics as columns (C characteristics). Each respondent has also a weight.
In case of high number of respondents, is it a good ... |
H: Setting class-weights in a batch in where a certain class is not present
I'm handling a high imbalanced dataset, thus, I'm weighing the loss function in order to penalize the misclassification of the minority classes, I set the weights in each batch as follows:
w[i] = num_total_instances / num_instances_of_class[i]... |
H: Lightweight binary image classifier
I want to build a fast binary classifier that decides if an image belongs to a given class (e.g. if it is a picture of a person). I want to do this by training a network on the RGB of pixels at a predetermined set of coordinates (e.g. 4 points, one near each corner of the image) ... |
H: CV hyperparameter in sklearn.model_selection.cross_validate
I've got a problem with understanding the CV parameter in cross_validate. Could you check if I understand it correctly?
I'm running ML algorithms in big set of data (train 37M rows), therefore I would like to run a big validation procedure to choose the b... |
H: Model-agnostic variable importance metric
I use genetic / evolutionary algorithms in python's TPOT package to find the overall best model (GBM, RF, SVM, elastic net, etc) and its tuning parameters. Now I need a way to measure each variable's contribution to the chosen model's predictive performance. How can I do th... |
H: Very Deep Convolutional Networks for Text Classification: Clarifying skip connections
Question RE this research paper if anyone has experience with CNN's, pooling & skip connections: https://arxiv.org/pdf/1606.01781.pdf
In figure 1, the input to the first convolutional block has shape (batch_size, 64, s)
The outpu... |
H: How to understand backpropagation using derivative
Before I was learning about gradient descent, but now I understand this. Now, I have a problem with the backpropagation algorithm. I know the idea - minimalize error in multilayer neural network using chain rule. However, I don't understand the role of the derivati... |
H: Bubbleplot with seaborn
Is there someway to create a bubble plot with seaborn? I already know how to do it with Matplot lib, as in this tutorial.
# libraries
import matplotlib.pyplot as plt
import numpy as np
# create data
x = np.random.rand(40)
y = np.random.rand(40)
z = np.random.rand(40)
# use the scatter fu... |
H: Keras/Theano custom loss calculation - working with tensors
I'm struggling to write some tensor manipulation code for a custom loss function I'm using in Keras.
Basically, I'm trying to modify a binary_crossentropy loss by adding a weight that is calculated from a particular feature.
First thing I do is pass in my ... |
H: XOR problem with neural network, cost function
I am having a problem understanding the cost function in a neural network. I have read many books and blog posts, but all of them describe that point in neural networks is to minimize the cost function (like sum squared error):
I tried to look at code for solving a pr... |
H: plot show relationship between independent variable and dependent variable(Binary)
My dependent variable is binary. Most of my independent variables are not. I am at the exploratory stage right now.
Y X1 X2
0 23 0
1 29 1
0 15 1
1 40 0
1 25 1
0 22 1
This is just a po... |
H: Knn and euclidean distance
I'm studying the knn classification algorithm.
Why can the euclidean distance be considered a nice measure of affinity between examples ?
In one dimension (1 attribute) this seems correct, but if I add dimensions, can the euclidean distance still be considerd a good measure of affinity? W... |
H: How to estimate the variance of regressors in scikit-learn?
Every classifier in scikit-learn has a method predict_proba(x) that predicts class probabilities for x. How to do the same thing for regressors?
The only regressor for which I know how to estimate the variance of the predictions is Gaussian process regres... |
H: How do we predict what is in an image using unsupervised deep neural networks?
From my understanding of unsupervised DNNs for image classification:
The input layer is a 4,096 dimension vector (for 64 x 64 images)
The hidden layers represent much lower "features" as identified by the back propagation
As the model i... |
H: Adding new variable to model
Let's say I already have a logistic regression model (or other) with N number of explanatory variables and is 70% accurate. Now if there are other variables available, how would I test if the new variables would improve my accuracy without building new model.
AI: I do not think you can ... |
H: Sklearn PCA with zero components example
I'm simply trying to repeat a benchmark from the sklearn's docs.
The unclear part is: n_components = np.arange(0, n_features, 5).
They are applying a PCA transform with 0 components!
Can somebody, please, explain, what's the mathematical meaning of this transform?
AI: Think... |
H: Why don't convolutional computer vision networks use horizontally - symmetric filters?
If, for example, I have a neural network for classifying dog breeds, and I feed it an image of some dog, inherently it shouldn't matter whether I feed it the original image or the image, mirrored horizontally.
I'd like to impleme... |
H: Grouping company information
I have 3 different datasets with company information, in all of them I have company name, but is not perfect: For example:
Dataset A: Company name: Facebook
Dataset B: Company name: Facebook, Inc
Dataset C: Company name: facebook
Some other signals like company url exists, but in term... |
H: Can AlphaGo Zero adapt to oponents skills/profile?
I read the AlphaGo Zero paper and I didn't found nothing about it in there. But I would like to know if AlphaGo Zero can adapt to the way the oponent plays (oponent profile) or something like this. Thanks!!
AI: But I would like to know if AlphaGo Zero can adapt to ... |
H: Using machine learning to optimize parameter scores
I have a dataset containing fraud and non fraudulent data. The system in place is a rule based engine with over 20 rules. If the total score is above a certain threshold the payment is classified as fraudulent.
What would be an effective way of using machine lear... |
H: Moving from macbook (without GPU) to linux system with Titan V, only getting a 4x speedup, what am I doing wrong?
I was prototyping a network architecture out on the macbook, and after finding something I was somewhat happy with, I wanted to test it out on a big data set on a system with a Titan V as the macbook wa... |
H: How do i interpret this correlation
Does this mean that as long as the student has good gpa and good gre even though his Alma Mater's prestige is low - he will get admitted in a college
Any additional things i can interpret from below ?
AI: No. From this correlation matrix you cannot draw the conclusion that
as lo... |
H: Simple prediction with Keras
I want to make simple predictions with Keras and I'm not really sure if I am doing it right. My data looks like this:
col1,col2
1.68,237537
1.69,240104
1.70,244885
1.71,246196
1.72,246527
1.73,254588
1.74,255112
1.75,259035
1.76,267229
1.77,267314
1.78,268931
1.79,273497
1.80,273900
1.8... |
H: TypeError: float() argument must be a string or a number, not 'function'
I am trying to clean the data. But I don't know how to remove a function from a column in data frame.
At row number 473 it show column N has a function . How it should be filtered out ?
AI: a generic way to convert pandas column to numeric dty... |
H: train_test_split : stratify can not be recognized?
I'm trying to set stratify = True, but somehow jupyter notebook says 'name 'y' is not defined'
X_train, X_test, y_train, y_test = train_test_split(
loan.drop('Loan_Status', axis=1),
loan['Loan_Status'], test_size=0.2, random_state=0, stratify=y)
Can anyon... |
H: How to scale prediction back after preprocessing
So I'm a newbie to machine learning and am currently using the iris data set. I ran through a quick online tutorial about predicting stock prices and thought I'd try and do the iris one myself.
The issue I'm having is that I'm using preprocessing to scale the data to... |
H: MLPRegressor Output Range
I am using Scikit's MLPRegressor for a timeseries prediction task.
My data is scaled between 0 and 1 using the MinMaxScaler and my model is initialized using the following parameters:
MLPRegressor(solver='lbfgs', hidden_layer_sizes=50,
max_iter=10000, shuffle=Fa... |
H: Clustering a labeled data set
I have a large labeled dataset with 29 classes. Is is possible to use a clustering algorithm (like k-means) in this dataset, or it's not possible since clustering algorithms are unsupervised ?
AI: You can do many things:
Forget about the labels: just use the features that are not labe... |
H: parquet format: advise on log content
I'm using a python script to log IO of a grid job.
the log is formatted like this:
timestamp;fullpath;event;size
1526994189.49;/tmp/folder/;IN_ISDIR;6
1526994189.49;/tmp/folder2/File;IN_ACCESS;36
Those files are millions of line long. I'm using Spark to generate graphs and de... |
H: GANs and grayscale imagery colorization
I am currently studying colorization of grayscale satellite imagery as part of my Master's internship. After looking for various machine learning techniques, I quickly decided to go for deep learning, as the colorization process can be completely automated and gives good resu... |
H: Precision and Recall if not binary
I have to calculate precision and recall for a university project to measure the quality of the classification output (with sklearn).
Say this would be my results:
y_true = [0, 1, 2, 1, 1]
y_pred = [0, 2, 1, 2, 1]
confusion matrix:
[1 0 0]
[0 1 2]
[0 1 0]
I have read about it a... |
H: Finding orthogonal input patterns associated with logistic function output
I've been given this problem but cannot seem to get an analytical solution. I've tried satisfying the logistic function with several vectors but have difficulty finding ones which are also orthogonal. The problem begins with me being given a... |
H: Supervised Learning could be biased if we use obsolete data
What if the data that we could use for the training is obsolete. For instance, if I train my model with the computer sales report from the 20th century and try to predict the actual trends, a disaster, right?
Another good example is the one that profiles c... |
H: Predicting which apps users may be interested in
I am building a mobile app that can predict what apps users may be interested in downloading from the play store, based on what apps the user has already installed on their device and how much time they have spent on these apps. Also, there is the option to scroll th... |
H: How to set class-weight for imbalanced classes in KerasClassifier while it is used inside the GridSearchCV?
Could you please let me know how to set class-weight for imbalanced classes in KerasClassifier while it is used inside the GridSearchCV?
# Use scikit-learn to grid search the batch size and epochs
from collec... |
H: Could someone explain to me how back-prop is done for the generator in a GAN?
I'm not very familiar with neural networks, however, I though I understood the concept of back propagation as starting from the error in the output layer. Say, we have 3 neurons in the output layer and their respective values end up being... |
H: Is this an over-fitting case?
I'm a new programmer and this is my first ever neural network for real world application.
Here is the deal, I'm using a top-less pre-trained VGG-16 with some dense layers on top of it.(for image classification problem)
But no matter what hyper parameters I change I always get plots s... |
H: How can I infer no target in a target classification problem based on deep learning?
Let's take the MNIST dataset (My application is different) with a lot of noise, I am going to train a deep NN to classify the letters.
What's the right way to infer, there's no letter possibility? or a letter not included in the tr... |
H: Difference between mathematical and Tensorflow implementation of Softmax Crossentropy with logit
Softmax cross entropy with logits can be defined as:
$a_i = \frac{e^{z_i}}{\sum_{\forall j} e^{z_j}}$
$l={\sum_{\forall i}}y_ilog(a_i)$
Where $l$ is the actual loss.
But when you look deep inside into C++ Tensorflow imp... |
H: Alternatives to imputation of missing values?
So I'm quickly learning that dealing with missing values for feature(s) in some of your observations is a part of every day life in data. I get the gist of imputation, when/how it's appropriate and when it's not, and I'll read up on it in the near future. But, what ab... |
H: What's wrong with my deep NN of two hidden layers?
batch_size = 128
size_1 = 1024
size_2 = 256
size_3 = 128
beta = 0.001
graph = tf.Graph()
with graph.as_default():
tf_train_dataset = tf.placeholder(
tf.float32,shape=(batch_size,image_size*image_size))
tf_train_labels = tf.placeholder(
... |
H: Handling binned feature
I am new to the field of data science and trying to figure out ways to handle data quality issues before performing any modeling.
I am working on a house rental price data set. In this data there is feature called Total Squarefeet. The issue I am facing here is that out of 12000 records 200... |
H: Dropout on inputs instead on outputs = DropConnect?
Is dropping out parts of the Input vector better than dropping out parts of the Output vector?
The latter literally makes this same neuron invisible to any further layers. On the contrary, ignoring pieces of the input means some of the further neurons will be abl... |
H: Normalising data with multiple methods
When training a neural network, I appreciate that data normalisation helps training. However, is it a good idea to normalise the data in multiple ways. For instance, is it a good idea to apply z-score normalisation on min-max normalised data? That is if the input data is alrea... |
H: How to predict class label from class probability given by predict_generator for testdata?
While using Keras' flow_from_directory method to train my model on a multi-class image classification problem, the predict_generator function gives the class probabilities.
So, my query is how to get the corresponding class-l... |
H: Resizing images for training with Mobilenets
I have a script to download images, but the images are of different resolutions so I have written a script to shrink the image. I have two options:
size=(224,224)
with cv2
cv2.resize(img,size,interpolation=cv2.INTER_AREA)
with PIL
img.thumbnail(size,Image.ANTIALIAS)
a... |
H: Really bad value of Val loss
I am using GTZAN dataset to make a CNN and classify by musical genres.
I'm getting very good results except Val. loss (See Image)
I am processing the audio files using Librosa, obtaining the spectogram and then using the power_to_db function.
This is my CNN Model:
class CNNModel(object... |
H: Reinforcement Learning in 2018, best tips and tricks?
Putting aside things applicable to neural networks such as dropout, l2 regularization, new opitmizers - what are the cool things I should be adding to my Reinforcement Learning algorithm (Q-Learning and SARSA) to make it stronger, in 2018?
So far, I know these:
... |
H: Web page data extraction using machine learning
I would like to extract some specific information from web pages. Web pages contain person profiles, and I want to extract information such as name, email, research interested-areas.
Structure of each page is different from one another. How can I extract such informa... |
H: Difficulty in choosing Hyperparameters for my CNN
My task is to estimate a person's age based on a face image of that person.
To that end I'm using a CNN and at first stage I was based on the following article: DeepExpectation which uses a VGG16 architecture to predict a person apparent age (the age that other peop... |
H: Trouble with accuracy of multiclass perceptron
I have built a multiclass perceptron, but it has low accuracy (around 80%). I think I'm missing something. One possibility is that I should add a bias, but I'm not sure how to incorporate that.
The task is, given 2 dimensions, predict the class, which is between 0 and ... |
H: What is the difference between bootstrapping and cross-validation?
I used to apply K-fold cross-validation for robust evaluation of my machine learning models. But I'm aware of the existence of the bootstrapping method for this purpose as well. However, I cannot see the main difference between them in terms of perf... |
H: How to normalize a boolean feature for neural nets?
I have a feature that is boolean and I would like to feed it to a neural net as one of the inputs. I think in theory the best is to encode as false->0 and true->1 because 0 as an input will deactivate weights of a neuron. Is this correct?
AI: Actually, it is not c... |
H: Time series feature extraction from raw sensor data for classification?
I have a tabular raw data from sensors with associated label and i want to extract the time series features like mean,max,min and std from the data all the sensor data and form another table or export to csv file so that i can do classification... |
H: Deep learning with Tensorflow: training with big data sets
Goal
I am trying to build a neural network that recognizes multiple label within a given image. I started with a database composed of 1800 images (each image is an array of shape (204,204,3). I trained my model and concluded that data used wasn't enough in ... |
H: How can I plot line plots based on an input python dataframe?
I need help to create a plot using 3 different columns from a dataframe. my dataframe looks like this:
index CMPGN_NM COST_SUM SUMRY_DT
2 GSA_SMB_SMB_Generic_BMM 8985 2018-05-17
3 GSA_SMB_SMB_Generic_BMM 7456 2018-05-18
4 GS... |
H: In which epoch should i stop the training to avoid overfitting
I'm working on an age estimation project trying to classify a given face in a predefined age range. For that purpose I'm training a deep NN using the keras library. The accuracy for the training and the validation sets is shown in the graph below:
As y... |
H: QGtkStyle could not resolve GTK
I have installed Orange 3 in Ubuntu 18.04 using Anaconda. It runs just fine, but the menus appear as blank.
I obtain the following error when I execute it:
QGtkStyle could not resolve GTK. Make sure you have installed the proper libraries.
I have been trying to sort it for days with... |
H: Export pandas to dictionary by combining multiple row values
I have a pandas dataframe df that looks like this
name value1 value2
A 123 1
B 345 5
C 712 4
B 768 2
A 318 9
C 178 6
A 321 3
I want to convert this i... |
H: How to check if audio samples have only noise or are silent?
I have a wav file I want to split into frames in order to feed it into a machine learning model. The problem is that the audio has silence with some noise at some points.
My problem is that I do not want to include frames with no sound (or only noise) in ... |
H: Isolation forest: how to deal with identical values?
I am trying to develop my own implementation of isolation forest algorithm. However I don't know how to deal with points that have the same value for a given feature. To better understand the problem, consider this example:
in my dataset I have the following data... |
H: How to use Scikit-learn's affinity propagation clustering with my own datasets?
I am trying to cluster my datasets using affinity propagation. I followed this and this links to grasp the basics of affinity propagation clustering. The sample code available at sklearn is as follows:
from sklearn.cluster import Affini... |
H: Getting same result for all predictions in cnn
This is my first time training a model in cnn and predicting results but I am getting same value for images I have input. Here is my code
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
from keras.datasets import mnist
from ker... |
H: Model's loss weights
I've model with two output layers, age and gender prediction layers. I want to assign different weight values for each output layer's loss. I've the following line of code to do so.
model.compile(loss=[losses.mean_squared_error,losses.categorical_crossentropy], optimizer='sgd',loss_weights=[1,... |
H: Naive Bayes for SA in Scikit Learn - how does it work
Okay so i scrape data from the web on movie reviews. I also have already got my own 'dictionary' or 'lexicon' with words and their labels (1-poor, 2-ok, 3-good, 4-very good, 5-excellent).
SO the input are paragraphs of movie reviews and i use Scikit Learn Naive... |
H: Accuracy reduces drastically when using TruncatedSVD with hashingvector
I have around 0.8 million product description with categories. There are around 280 categories. I want to train a model with given dataset so that in future I can predict Category for the given product description. Since the dataset was large I... |
H: Predictive modeling on time series: How far should I look back?
I am building a model for classification on a dataset which is collected by recording a system's behaviour through 2 years period of time. The model is going to be used in the same system in real time.
Right now I am using the whole dataset (2 years) t... |
H: GAN to generate a custom image does not work
I have been training a GAN in the cloud for some time now. I use Google's free credit. My laptop with a CPU doesn't seem to be up to the task.
The image I want to generate is this.
Even though the number of epochs is about 15000 I don't get anything close to the origina... |
H: Dimensions For Matrix Multiplication
Can anyone explain why the following code produces input_t with a shape of (32,) instead of (,32), given the fact that inputs has a shape (100, 32)? Shouldn't input_t produce a vector with 32 attributes/columns?
import numpy as np
timesteps = 100
input_features = 32
output_feat... |
H: Determine useful features for machine learning model
I am working with a dataset with hundreds of features. I wish to create a simple machine learning model using 7-10 features from the original dataset. My question is this:
What quantitative metrics can I use to determine that a feature will be useful to the learn... |
H: which deep learning text classifier is good for health data
I have a data set like this:
postID Sentence drugYesOrNo
1 He went out with his friends
2 He behaved nicely while talking with me
3 He stopped using drugs after a while 1
4 ... |
H: Storing engineered features in a database
I have some data in raw csv files which I would like to store in a MySQL database. The problem is there are constant feature engineering done on this dataset so coming up with one schema to fit all the needs is not possible. The approach I thought of was to have one main ... |
H: Least Squares Regression $Ax=b$ when $A$ is fixed and $b$ is varied
The typical setting for least squares regression (or over-determined linear system) for $Ax=b$ is to solve $x$ given $A$ and $b$.
In other words, $A$ and $b$ are fixed when we solve the problem.
My question is that is there any application that $... |
H: Which convolution should I use? Conv2d or Conv1d
I've dataset which contains dlib landmark points of the faces. I'm using keras to train a model.
The dataset shape is (length_of_dataset,68,2). I know that I've two options.
The first is using conv1d with input_shape = (68,2).
The second is using conv2d with input_s... |
H: Implement Sliding Window Algorithm to Detect Spikes
How do I implement sliding window algorithm with a window size of 10 and visualize the data iteratively to see spikes/possible outliers in the dataframe, using python? Please help a beginner.
AI: welcome to DS-SE and to Data Science in general! :)
Your problem can... |
H: How to learn Machine Learning
I want to get into machine learning. I've been in information security for the last 10 years so i have an IT background.
Where is the best place to start:
Can anyone recommend a good book? And also a platform i can use to practice (preferably free)
Also if there are any online courses ... |
H: Making bigram features from a particular dataset
I have a folder which has a number of files which have a format like these
madvise
write
write
write
write
read
read
madvise
ioctl
ioctl
getuid
epoll_pwait
read
recvfrom
sendto
getuid
epoll_pwait
that is it is a set of words which repeat.This is how all the files a... |
H: Tools to explore various datasets
TL:DR - Do you know of good automated tools to explore a dataset?
Long version: I have a few different datasets to work with from most various areas of business. I wonder if there are good software/scrips that could automatically round up the following answers for me:
Things I woul... |
H: How to select the learned model using $k$-fold cross validation?
Let us consider a case where $1000$ data is given, i.e., the data set $U=\{x_1, \ldots, x_{1000}\}.$
When we want to use $k$-fold validation scheme, we first divide the data set into $k$ groups.
With out loss of generality, the parameter $k$ is assume... |
H: Why my neural network does not predict decimal values in range [-1,1]? When it is able to predict the integer values
I am trying to perform a very simple experiment, predict the input number. The concept is same as an auto-encoder. But with just one layer, which can handle the task of encoding and decoding-
Also, w... |
H: Can you provide examples of business application of vector autoregressive model?
Vector Autoregressive models are exploited at Economics faculties all around the world. They are just another statistical model that solves problem of forecasting, although in a deeply complexity-uncovering manner.
Yet to my surprise, ... |
H: How can I evaluate data mining model?
I will evaluate classification models I made. That's logistic regression and decision tress.
1. What I use standards for comparison?
2. Suppose model selection's standard is ASE. One is high ASE of training data, low ASE of test data, and the other is ASE of training data is l... |
H: Numerical example of Confusion in understanding learning rate in xgboost
I fail to understand as to how learning rate is used in XGBoost?
Can anyone explain using a numerical example?
AI: Each iteration is supposed to provide an improvement to the training loss.
Such improvement is multiplied with the learning rate... |
H: Regression equation for ordinal data
I'm doing research where a part of the collected data is of Ordinal type. I will implement ANN with Logistic Regression function in the Activation function. What I have learnt from documents of other websites as well as an answer in https://datascience.stackexchange.com/, the ta... |
H: Why is it important to have sufficient number of instances in your dataset for each stratum?
As per the figure 1, most of the median-income values are clustered around \$20,000-\$50,000, but some median incomes go far beyond \$60,000.
I didn't understand the explanation behind why housing['median_income'] has to... |
H: What is the exact definition of VC dimension?
I'm studying machine learning from Andrew Ng Stanford lectures and just came across the theory of VC dimensions. According to the lectures and what I understood, the definition of VC dimension can be given as,
If you can find a set of $n$ points, so that it can be sha... |
H: Computer Vision: Handling dataset(3D data or scan) with different timesteps
I'm planning on training a CNN on CT scans for classification. The problem is CT scans are taken slice by slice, and in a typical scan, there could be more than 200 slices. The number of slices in a scan isn't uniform and depend on the scan... |
H: ML model to transform words
I build model that on input have correct word. On output there is possible word written by human (it contain some errors). My training dataset looks that:
input - output
hello - helo
hello - heelo
hello - hellou
between - betwen
between - beetween
between - beetwen
between ... |
H: Chi-squared for continuous variables
I am using chi-squared to determine feature importance as I select features to train a supervised ML model. I create a contingency table for the feature/target, and feed this contingency table into the scipy.stats.chi2_contingency module. This module returns the chi-squared valu... |
H: Need help in understanding a small example
Pardon me, I agree the title of the question is not clear. I would like to know the understanding of below steps which are picked from the textbook "Hands on machine learning".
>>> housing['income_cat'].value_counts()
>>> 3.0 7236
2.0 6581
4.0 3639
... |
H: Does matrix shape for training/testing sets have to be in a particular order?
I've noticed that in the Andrew Ng Deep Learning course that for image analysis he always has X_train matrices in the shape of [height, width, 3, num_inputs], or, if flattened, [height X width X 3, num_inputs]. He also has his y_train as ... |
H: How to set class weights for imbalanced classes in Tensorflow?
Do we have an equivalence for the following question, but with tensorflow : How to set class weights for imbalanced classes in Keras? ??
AI: There's a function that does it automatically: tf.contrib.losses.softmax_cross_entropy(logits, onehot_labels, we... |
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