model

问题 I have trained my own word2vec model in gensim and I am trying to load that model in spacy. First, I need to save it in my disk and then try to load an init-model in spacy but unable to figure out exactly how. gensimmodel Out[252]: <gensim.models.word2vec.Word2Vec at 0x110b24b70> import spacy spacy.load(gensimmodel) OSError: [E050] Can't find model 'Word2Vec(vocab=250, size=1000, alpha=0.025)'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory. 回答1:

问题 I have trained my own word2vec model in gensim and I am trying to load that model in spacy. First, I need to save it in my disk and then try to load an init-model in spacy but unable to figure out exactly how. gensimmodel Out[252]: <gensim.models.word2vec.Word2Vec at 0x110b24b70> import spacy spacy.load(gensimmodel) OSError: [E050] Can't find model 'Word2Vec(vocab=250, size=1000, alpha=0.025)'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory. 回答1:

问题 I have the following Python dataframe: Type Actual Predicted A 4 3 A 10 18 A 13 11 B 3 10 B 4 2 B 8 33 C 20 17 C 40 33 C 87 80 C 32 30 I have the code to calculate R^2 and RMSE but I don't know how to calculate it by distinct "Type". For now, my methodology is breaking the larger table into three smaller tables consisting of only A, B, C values and then calculating R^2 and RMSE off each smaller table...then appending them back together. But the above method is inefficient and I believe there

问题 I have the following Python dataframe: Type Actual Predicted A 4 3 A 10 18 A 13 11 B 3 10 B 4 2 B 8 33 C 20 17 C 40 33 C 87 80 C 32 30 I have the code to calculate R^2 and RMSE but I don't know how to calculate it by distinct "Type". For now, my methodology is breaking the larger table into three smaller tables consisting of only A, B, C values and then calculating R^2 and RMSE off each smaller table...then appending them back together. But the above method is inefficient and I believe there

问题 I am new to Django and Python and I want to do something I used to do very often in Java EE. Consider the following model (only relevant classes): class Item(models.Model): name = models.CharField(max_length=40) default_price = models.DecimalField(max_digits=6, decimal_places=2, default=50) def __unicode__(self): return self.name class SaleDetail(models.Model): item = models.ForeignKey(Item) deposit = models.ForeignKey(Deposit) quantity = models.PositiveIntegerField() unit_price = models

问题 I am trying to freeze a flow pattern In tenorflow, training from scratch is created after 4 files: model.ckpt-454501.data-00000-of-00001 model.ckpt-454501.index model.ckpt-454501.meta checkpoint I would like to convert them (or only the needed ones) into one file graph.pb I use src : import tensorflow as tf meta_path = 'model.ckpt-454501.meta' # Your .meta file # output_node_names = ['output:0'] # Output nodes with tf.Session() as sess: # Restore the graph saver = tf.train.import_meta_graph

问题 When developing Java Swing MVC apps, what is a GUI model in opposition to an Application Model? And why is it relevant to MVC? I read about it the example here (the example does not use a GUI model though). Found more information about it here, here and here. Also in A Swing Architecture Overview in the section GUI-state vs. application-data models . To cite the author of the example: Finally, this is how I implement the model / view / controller pattern (MVC) in Java Swing. The view may read

问题 In Django model I am making a table 'followers', which has: user's id. (this is followed by) user's id (this is follower) that's simple a user can follow other users. How should I define the model in Django? I tried this, but does not work: user = models.ForeignKey('self') follower_id = models.ForeignKey('self') How should this be done? thanks 回答1: The 'self' argument won't work unless you have a model called self . Assuming that your assignment model is called Following , and you're using

问题 The --passes flag is the number of training passes. But it's unclear what the notion of passes means when training a Python VW model, within a for loop for example. e.g. If I'm training a model example by example within a for-loop like this: for line in train: model.learn(line) How could there be multiple passes if each training sample is learned from only once? 回答1: In Python the passes option only affect when the inbuilt driver is used. This only occurs when a data file and or passes is

问题 The --passes flag is the number of training passes. But it's unclear what the notion of passes means when training a Python VW model, within a for loop for example. e.g. If I'm training a model example by example within a for-loop like this: for line in train: model.learn(line) How could there be multiple passes if each training sample is learned from only once? 回答1: In Python the passes option only affect when the inbuilt driver is used. This only occurs when a data file and or passes is