You can use the words corpus from NLTK: import nltk words = set(nltk.corpus.words.words()) sent = “Io andiamo to the beach with my amico.” ” “.join(w for w in nltk.wordpunct_tokenize(sent) \ if w.lower() in words or not w.isalpha()) # ‘Io to the beach with my’ Unfortunately, Io happens to be an English word. In general, it … Read more
Just to answer this question in a little more detail, and as Pavel said, Batch Normalization is just another layer, so you can use it as such to create your desired network architecture. The general use case is to use BN between the linear and non-linear layers in your network, because it normalizes the input … Read more
You can groupby and use agg to get the mean. For the non numeric columns, let’s take the first value: df.groupby(‘Player’).agg({k: ‘mean’ if v in (‘int64’, ‘float64’) else ‘first’ for k,v in df.dtypes[1:].items()}) output: Pos Age Tm G GS MP FG Player Jarrett Allen C 22 TOT 18.666667 6.666667 26.266667 4.333333 NB. content of the … Read more
In stratKFolds, each test set should not overlap, even when shuffle is included. With stratKFolds and shuffle=True, the data is shuffled once at the start, and then divided into the number of desired splits. The test data is always one of the splits, the train data is the rest. In ShuffleSplit, the data is shuffled … Read more
A simple example which encodes an array using LabelEncoder, OneHotEncoder, LabelBinarizer is shown below. I see that OneHotEncoder needs data in integer encoded form first to convert into its respective encoding which is not required in the case of LabelBinarizer. from numpy import array from sklearn.preprocessing import LabelEncoder from sklearn.preprocessing import OneHotEncoder from sklearn.preprocessing import … Read more
I am the developer of OSMnx. There is a growing amount of misinformation and confusion in this thread, so I will give you a definitive answer. Just follow the documented installation instructions to install the latest release of OSMnx: conda config –prepend channels conda-forge conda create -n ox –strict-channel-priority osmnx If you install an old … Read more
Several column names may be provided to the y argument of the pandas plotting function. Those should be specified in a list, as follows. df.plot(x=”year”, y=[“action”, “comedy”]) Complete example: import matplotlib.pyplot as plt import pandas as pd df = pd.DataFrame({“year”: [1914,1915,1916,1919,1920], “action” : [2.6,3.4,3.25,2.8,1.75], “comedy” : [2.5,2.9,3.0,3.3,3.4] }) df.plot(x=”year”, y=[“action”, “comedy”]) plt.show()
In general, the error ValueError: Wrong number of items passed 3, placement implies 1 suggests that you are attempting to put too many pigeons in too few pigeonholes. In this case, the value on the right of the equation results[‘predictedY’] = predictedY is trying to put 3 “things” into a container that allows only one. … Read more
I was faced with the same issue in windows 10, Updating the environment variable following steps, it’s working fine. I know It is a lengthy answer for the simple environment setups, I thought it’s may be useful for the new window 10 users. 1) Open Anaconda Prompt: 2) Check Conda Installed Location. where conda 3) … Read more
This is likely due to your system’s overcommit handling mode. In the default mode, 0, Heuristic overcommit handling. Obvious overcommits of address space are refused. Used for a typical system. It ensures a seriously wild allocation fails while allowing overcommit to reduce swap usage. The root is allowed to allocate slightly more memory in this … Read more