machine-learning

问题 I am getting this error: ValueError: Items of feature_columns must be a _FeatureColumn. Given (type ): Index(['CreditScore', 'Age', 'Tenure', 'Balance', 'NumOfProducts', 'HasCrCard', 'IsActiveMember', 'EstimatedSalary', 'Exited'], dtype='object'). I am using tensorFlow lib. I want to get prediction results but I can not run m.train(input_fn=get_input_fn ,steps=5000) code. I always got the same error whatever I did. I used these input functions in the following but nothing changed. def input

问题 I'm attempting to create my own dataset for use with YOLO (You Only Look Once). Initially, I started with a large geotiff file that had pictures of landscape and animals. I was able to write a script to extract the images of the animals into separate files. I'm now at a point where I'd like to use those animal images as part of a YOLO dataset. However, all of the examples I've seen online utilize annotation files, which denote the location of an object-to-be-detected within a larger image. In

问题 I'm trying to build a custom keras model whith the subclassing API but I get some errors when I load a previous instance of my model and I try to train it : Here is the class of my model, it has 3 inputs and 1 output : import tensorflow as tf spec1 = tf.TensorSpec(shape=(1,40,5,1)) spec2 = tf.TensorSpec(shape=(1,3)) class Conv_Rnn_model(tf.keras.Model): def __init__(self): # super() permet d'appeler le constructeur de la classe mère dans la classe fille # permet égalemet de résoudre le

问题 I'm trying to build a custom keras model whith the subclassing API but I get some errors when I load a previous instance of my model and I try to train it : Here is the class of my model, it has 3 inputs and 1 output : import tensorflow as tf spec1 = tf.TensorSpec(shape=(1,40,5,1)) spec2 = tf.TensorSpec(shape=(1,3)) class Conv_Rnn_model(tf.keras.Model): def __init__(self): # super() permet d'appeler le constructeur de la classe mère dans la classe fille # permet égalemet de résoudre le

问题 I'm trying to build a custom keras model whith the subclassing API but I get some errors when I load a previous instance of my model and I try to train it : Here is the class of my model, it has 3 inputs and 1 output : import tensorflow as tf spec1 = tf.TensorSpec(shape=(1,40,5,1)) spec2 = tf.TensorSpec(shape=(1,3)) class Conv_Rnn_model(tf.keras.Model): def __init__(self): # super() permet d'appeler le constructeur de la classe mère dans la classe fille # permet égalemet de résoudre le

问题 I'm trying to build a custom keras model whith the subclassing API but I get some errors when I load a previous instance of my model and I try to train it : Here is the class of my model, it has 3 inputs and 1 output : import tensorflow as tf spec1 = tf.TensorSpec(shape=(1,40,5,1)) spec2 = tf.TensorSpec(shape=(1,3)) class Conv_Rnn_model(tf.keras.Model): def __init__(self): # super() permet d'appeler le constructeur de la classe mère dans la classe fille # permet égalemet de résoudre le

问题 I have the following code below which simply plots datasets (consisting of dogs and cats images) and their labels. I'm using jupyter notebook: train_path = 'dataset/train' valid_path = 'dataset/valid' test_path = 'dataset/test' train_batches = ImageDataGenerator().flow_from_directory(train_path, target_size=(224,224), classes=['dog', 'cat'], batch_size=10) valid_batches = ImageDataGenerator().flow_from_directory(valid_path, target_size=(224,224), classes=['dog', 'cat'], batch_size=4) test

问题 How can I compare a Tensorflow string tensor to a python string type. I tried something like this if(tf.constant("neg",tf.string) in key): a=True key here, is a tf.string. I want to see if 'neg' is in the key tensor. 回答1: Unfortunately, currently you cannot. Please ask this on TF github in issues section. 来源： https://stackoverflow.com/questions/35946810/compare-tf-string-and-python-string

问题 How can I compare a Tensorflow string tensor to a python string type. I tried something like this if(tf.constant("neg",tf.string) in key): a=True key here, is a tf.string. I want to see if 'neg' is in the key tensor. 回答1: Unfortunately, currently you cannot. Please ask this on TF github in issues section. 来源： https://stackoverflow.com/questions/35946810/compare-tf-string-and-python-string

问题 I have been given 2 data sets and want to perform cluster analysis for the sets using KNIME. Once I have completed the clustering, I wish to carry out a performance comparison of 2 different clustering algorithms. With regard to performance analysis of clustering algorithms, would this be a measure of time (algorithm time complexity and the time taken to perform the clustering of the data etc) or the validity of the output of the clusters? (or both) Is there any other angle one look at to