pipeline

问题 I do as below import pandas as pd from sklearn import preprocessing import sklearn from sklearn.pipeline import Pipeline df = pd.DataFrame({'c':['a', 'b', 'c']*4, 'd': ['m', 'f']*6}) encoding_pipeline =Pipeline([ ('LabelEncoder', preprocessing.LabelEncoder()) ]) encoding_pipeline.fit_transform(df) and full Traceback TypeError Traceback (most recent call last) <ipython-input-7-0882633ccf59> in <module>() ----> 1 encoding_pipeline.fit_transform(df) C:\Program Files\Anaconda3\lib\site-packages

问题 I've written some pwsh code "a:b;c:d;e:f".Split(";") | ForEach-Object { $_.Split(":") } # => @(a, b, c, d, e, f) but I want this // in javascript "a:b;c:d;e:f".split(";").map(str => str.split(":")) [ [ 'a', 'b' ], [ 'c', 'd' ], [ 'e', 'f' ] ] a nested array @( @(a, b), @(c, d), @(e, f), ) Why? and what should I do 回答1: Use the unary form of , , PowerShell's array-construction operator: "a:b;c:d;e:f".Split(";") | ForEach-Object { , $_.Split(":") } That way, the array returned by $_.Split(":")

问题 I want to pipe the output of a command to a file: PS C:\Temp> create-png > binary.png I noticed that Powershell changes the encoding and that I can manually give an encoding: PS C:\Temp> create-png | Out-File "binary.png" -Encoding OEM However there is no RAW encoding option, even the OEM option changes newline bytes ( 0xA resp 0xD ) to the windows newline byte sequence ( 0xD 0xA ) thereby ruining any binary format. How can I prevent Powershell from changing the encoding when piping to a file

问题 I want to pipe the output of a command to a file: PS C:\Temp> create-png > binary.png I noticed that Powershell changes the encoding and that I can manually give an encoding: PS C:\Temp> create-png | Out-File "binary.png" -Encoding OEM However there is no RAW encoding option, even the OEM option changes newline bytes ( 0xA resp 0xD ) to the windows newline byte sequence ( 0xD 0xA ) thereby ruining any binary format. How can I prevent Powershell from changing the encoding when piping to a file

问题 Given the dplyr workflow: require(dplyr) mtcars %>% tibble::rownames_to_column(var = "model") %>% filter(grepl(x = model, pattern = "Merc")) %>% group_by(am) %>% summarise(meanMPG = mean(mpg)) I'm interested in conditionally applying filter depending on the value of applyFilter . Solution For applyFilter <- 1 the rows are filtered with use of the "Merc" string, without the filter all rows are returned. applyFilter <- 1 mtcars %>% tibble::rownames_to_column(var = "model") %>% filter(model %in%

问题 I'm using a Scikit-Learn custom pipeline ( sklearn.pipeline.Pipeline ) in conjunction with RandomizedSearchCV for hyper-parameter optimization. This works great. Now I would like to insert a Keras model as a first step into the pipeline. Parameters of the model should be optimized. The computed (fitted) Keras model should then be used later on in the pipeline by other steps, so I think I have to store the model as a global variable so that the other pipeline steps can use it. Is this right? I

问题 I'm getting a number of errors, depending upon what is being inserted/updated. Here is the code for processing the item: def process_item(self, item, spider): try: if 'producer' in item: self.cursor.execute("""INSERT INTO Producers (title, producer) VALUES (%s, %s)""", (item['title'], item['producer'])) elif 'actor' in item: self.cursor.execute("""INSERT INTO Actors (title, actor) VALUES (%s, %s)""", (item['title'], item['actor'])) elif 'director' in item: self.cursor.execute("""INSERT INTO

问题 I'm trying to code a visualization pipeline in VisJs. So I have a graph and some nodes. The nodes can generate/use a few different data types. So I need something like this ------------------ | Node1 | ------------------ int char | | | | | | | | int string char ------------------ | Node2 | ------------------ So one node has more than 1 anchor points that only connect to it's own type. Can I change the location from where the edges are drawn to where they are connected in the node? Does anyone

问题 I have been working on a React web app and I need to deploy it now. I have the codebase in GitLab and I'm using Gitlab pipeline to run the tests and create build and deploy. For deployment I need to deploy it to a EC2 instance. My pipeline runs well until creating the build. Now the problem is how to push that created build to the EC2 instance. Can someone help me in here. I tried in the following way. Gitlab CI deploy AWS EC2 It showed me connection time out message instead of connecting to

问题 In the following sequence of MIPS instructions (entire program not shown): DADDUI R1, R1, #-8 BNE R1, R2, Loop I want to confirm the number of stalls required between the two instructions (in context of 5 stage MIPS pipeline - IF, ID/Reg, EX, MEM, WB) with and without forwarding. My understanding: (a) If there is no forwarding: In this case, 2 stalls are required (in cycle 5, R1 can be read in the ID stage for second instruction using split phase access for registers) (b) If there is