kandi X-RAY | Iris Summary
kandi X-RAY | Iris Summary
(WIP) A modern shaders mod for Minecraft intended to be compatible with existing OptiFine shader packs
Top functions reviewed by kandi - BETA
- Determine the intersection of a sphere
- Test whether a point is inside a triangle
- Computes the lowest root root of the quadratic equation
- Determines the intersection of a sphere
- Computes the lowest root of the quadratic
- Rotates the given object matrix
- Apply the transformation of an object to a sphere
- Performs the actual transformation on the AST
- Converts a shader type to an array of patches
- Finds the closest points on a line segment
- Returns the closest point on the two line segments
- Compute the perspective transformation
- Computes the perspective transformation
- Rotates a cylindrical matrix
- Compute the direction of the frustum
- Computes the direction of the frustum plane
- Test if an intersecting box
- Computes the weighted average of all the quaternions
- Finds the closest point on a line segment
- Test to see if a sphere is found
- Computes and returns a projection matrix that covers the specified plane
- Transforms each AST node in a VERT declaration
- Computes the weighted average of all quaternions in the given order
- Computes the projected grid range
- Updates the frustum rectangle with the given matrix
- Creates a custom texture
Iris Key Features
Iris Examples and Code Snippets
def main(): """ Random Forest Classifier Example using sklearn function. Iris type dataset is used to demonstrate algorithm. """ # Load Iris dataset iris = load_iris() # Split dataset into train and test data X = ir
Trending Discussions on Iris
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...
ANSWERAnswered 2021-Jun-15 at 13:10
$ inside functions, we can use
[[ to extract a particular columns.
You can modify the function as follows -
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...
ANSWERAnswered 2021-Jun-15 at 02:27
dat <- iris[iris$Sepal.Length > 6.5, ] nrow(dat)
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:...
ANSWERAnswered 2021-Jun-14 at 07:45
You can use the following -
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.
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:
ANSWERAnswered 2021-Jun-14 at 16:10
We can use
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...
ANSWERAnswered 2021-Jun-14 at 15:15
Three options:base graphics
Determine the y range before plotting. For this there are two options, choose from one of the
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?...
ANSWERAnswered 2021-Jun-14 at 14:52
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:
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:...
ANSWERAnswered 2021-Apr-27 at 16:28
It is because you only specify 3 values, but you have many more points. One way to do this is to specify every point:
Using the iris dataset in R, I write a function to plot a confusion matrix....
ANSWERAnswered 2021-Jun-12 at 09:19
You can create separate column for labels. For 0 frequency make them as blank.
BRAND new to ML. Class project has us entering the code below. First I am getting warning:...
ANSWERAnswered 2021-Jun-12 at 04:26
You 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
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
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
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
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
After that, I get the following:
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:...
ANSWERAnswered 2021-Jun-11 at 12:52
When 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.
No vulnerabilities reported
You can use Iris like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Iris component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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