Iris | music library across multiple sources with this beautiful | Music Player library
kandi X-RAY | Iris Summary
kandi X-RAY | Iris Summary
Discover, explore and manage your music library across multiple sources with this beautiful web-based interface. Iris is a Mopidy frontend extension.
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QUESTION
I am creating a function that runs through my variables and determines if they are numeric. If the variable is numeric, I want it to print the mean, median, variance, mode and range. And if it is not numeric, I want it to print just the mode. However it doesn't work not sure if I am using the right function (typeof & class)
I receive below error
...ANSWER
Answered 2021-Jun-15 at 13:10Don't use $
inside functions, we can use [[
to extract a particular columns.
You can modify the function as follows -
QUESTION
From the “iris” dataset, how to find the number of observations whose “Sepal.Length” is greater than ‘6.5’ Using only loops or conditional statements
...ANSWER
Answered 2021-Jun-15 at 02:27dat <- iris[iris$Sepal.Length > 6.5, ]
nrow(dat)
QUESTION
I want to generate one column in data with previous value if the condition in if_else are/aren`t consistent with, the value will be the same as the original column.
Here is the code:
...ANSWER
Answered 2021-Jun-14 at 07:45You can use the following -
QUESTION
This is a simplified version of the actual problem I'm dealing with. In this example, I'll be working with four columns, and the actual problem requires working with about 20-30 columns.
Consider the iris
dataset. Suppose that I wanted to, for some reason, append new columns which would be equal to double the .Length
and the .Width
columns. With the following code, this would change the existing columns:
ANSWER
Answered 2021-Jun-14 at 16:10We can use across
(used dplyr
1.0.6
version)
QUESTION
I work with the iris dataset, the aim is to get 4 boxplots next to each other and make them all share an y-axis that goes from 0 to 8
...ANSWER
Answered 2021-Jun-14 at 15:15Three options:
base graphicsDetermine the y range before plotting. For this there are two options, choose from one of the ylim=
below:
QUESTION
I'm trying to compute shap values using DeepExplainer, but I get the following error:
keras is no longer supported, please use tf.keras instead
Even though i'm using tf.keras?
...ANSWER
Answered 2021-Jun-14 at 14:52TL;DR
- Add
tf.compat.v1.disable_v2_behavior()
at the top for TF 2.4+- calculate shap values on numpy array, not on df
Full reproducible example:
QUESTION
Is there a way to match ggplot geom_point position dodging width to a geom_boxplot width that is adjusted to the number of data points using the varwidth = TRUE option in geom_boxplot? This would require different dodging widths for each group. Demonstration:
...ANSWER
Answered 2021-Apr-27 at 16:28It is because you only specify 3 values, but you have many more points. One way to do this is to specify every point:
QUESTION
Using the iris dataset in R, I write a function to plot a confusion matrix.
...ANSWER
Answered 2021-Jun-12 at 09:19You can create separate column for labels. For 0 frequency make them as blank.
QUESTION
BRAND new to ML. Class project has us entering the code below. First I am getting warning:
...ANSWER
Answered 2021-Jun-12 at 04:26You need to set self.theta
to be an array, not a scalar (at least in this specific problem).
In your case, (intercepted-augmented) X
is a '3 by n' array, so try self.theta = [0, 0, 0]
for example. This will correct the specific error 'bool' object has no attribute 'mean'
. Still, this will just produce preds as a zero vector; you haven't fit the model yet.
To let you know how I approached the error, I first went to the exact line the error message was pointing to, and put print(preds == y)
before the line, and it printed out False
. I guess what you expected was a vector of True
and False
s. Your y
seemed okay; it was a vector (a list
to be specific). So I tried print(pred)
, which showed me a '3 by n' array, which is weird. Now going up from that line, I found out that pred
comes from predict_prob()
, especially np.dot(X, self.theta)
. Here, when X
is a '3 by n' array and self.theta
is a scalar, numpy seems to multiply the scalar to each item in the array and return the array (having the same dimension as the original array), instead of doing matrix multiplication! So you need to explicitly provide self.theta
as an array (conforming to the dimension of X
).
Hope the answer and the reasoning behind it helped.
As for the red line you mentioned in the comment, I guess it is also because you are not fitting the model. (To see the problem, put print(probs)
before plt.countour(...)
. You'll see an array with 0.5 only.)
So try putting model.fit(X, y)
before preds = model.predict(X)
. (You'll also need to put self.verbose = verbose
in the __init__()
.)
After that, I get the following:
QUESTION
Based on the guide Implementing PCA in Python, by Sebastian Raschka I am building the PCA algorithm from scratch for my research purpose. The class definition is:
...ANSWER
Answered 2021-Jun-11 at 12:52When calculating an eigenvector you may change its sign and the solution will also be a valid one.
So any PCA axis can be reversed and the solution will be valid.
Nevertheless, you may wish to impose a positive correlation of a PCA axis with one of the original variables in the dataset, inverting the axis if needed.
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