Hi Scikit fans,
I want to combine multiple forests with same no. of samples but different
no. of features.
For e.g. Here are two estimators of random forest with different no. of
features:
estimator =
RandomForestClassifier(n_estimators=best_n_estimators,max_depth=best_max_depth,random_state=0)
Hi guys,
I want to check the overfitting/under-fitting of the RF model classifier.
I have plotted learning curve to for this purpose. I have 2 classes in 1:1
ration in my training data and I have used StratifiedShuffleSplit for 10
iterations. Based on the scores, I found it as a good training
Hi guys,
I want to check the overfitting/under-fitting of the RF model classifier.
I have plotted learning curve to for this purpose. I have 2 classes in 1:1
ration in my training data and I have used StratifiedShuffleSplit for 10
iterations. Based on the scores, I found it as a good training
Hey Guys,
Though I have scikit learn installed, but I am unable to import this module:
from sklearn.learning_curve import learning_curve
ImportError: No module named learning_curve
I googled it and found that it has some incompatibility with python
version:
Hi guys,
I'm facing a problem when I am using decision_function in svm classifier. I
have *2 classes*, but decision function is returning an array with *one
column* only. Decision_function is working fine with iris dataset. I'm
afraid if I am doing something wrong while reading my files/data.
calibrated, too.
iv) Use k-fold cross validation. (
http://scikit-learn.org/stable/modules/cross_validation.html)
Best,
Sebastian
On Feb 26, 2015, at 8:00 AM, shalu jhanwar shalu.jhanwa...@gmail.com
wrote:
Hey guys,
Would you like to comment on them according to your exp.?
i) if both
Hey guys,
Would you like to comment on them according to your exp.?
i) if both the classes are having same probability (0.5), then which class
would be predicted by Random Forest?
ii) In my classification, I have seen more false predictions corresponding
to the positive class by my model. Can
. Iris dataset contains 3 classes, so
there are 3 possible pairs, and thus 3 columns in the result of
decision_function.
On Thu, Feb 26, 2015 at 7:28 PM, shalu jhanwar shalu.jhanwa...@gmail.com
wrote:
Hi guys,
I'm facing a problem when I am using decision_function in svm classifier.
I have
it to be consistent.
Just remove the second call to fit.
On 02/25/2015 06:35 AM, shalu jhanwar wrote:
Hey Guys,
I am using Random forest classifier to perform binary classification on
my dataset. I wanted to have a confidence value of both the classes
corresponding to each sample. For that purpose
of
predict_proba, so I'd be very surprised if they are not consistent.
Cheers,
Andy
On 02/25/2015 08:33 AM, shalu jhanwar wrote:
Hi all,
I'm facing the same problem with predict_proba for Random_forest
classifier. I want to get a confidence value for each class and each
prediction
0.42
Please let me know still am I missing something??
thanks!
Shalu
On Wed, Feb 25, 2015 at 9:53 PM, shalu jhanwar shalu.jhanwa...@gmail.com
wrote:
Hi guys!
Ahh, ok, I check it and will confirm you.
thanks!
Shalu
On Wed, Feb 25, 2015 at 9:32 PM, Andy t3k
It didn't work Andy, even after that...
I removed refitting the data, but didn't set random_state explicitly. The
same problem persist. Look at these few examples:
Y_true Y_predict Class0_prob. Class1_prob.
1 0 0.28 0.72
Hi Andy,
please find this version of the code in which I changed the refit issue.
thanks!
Shalu
On Wed, Feb 25, 2015 at 11:35 PM, shalu jhanwar shalu.jhanwa...@gmail.com
wrote:
Hi Andy,
Please see the code. Hereby I am attaching following files:
i) Code
#sklearn.metrics.auc(fpr[micro],
tpr[micro])
I'm just using this default code, but I would like to know about the
threshold it uses to generate each point of ROC
thanks!
Shalu
On Fri, Feb 20, 2015 at 5:27 PM, shalu jhanwar shalu.jhanwa...@gmail.com
wrote:
Hi Sebastian,
Thanks a lot for your reply. Here
Yeah ..it's here.
thanks for the explanation.
S.
On Sun, Feb 22, 2015 at 10:57 PM, Andy t3k...@gmail.com wrote:
I think it is. The last character of my answer was _.
That is the variable name to which you assign the thresholds in your code.
On 02/22/2015 01:54 PM, shalu jhanwar wrote
Hi Andy,
thanks for the reply. I guess your second question's ans. is not completely
displayed in the email. Could you please re-post it?
thanks!
S.
On Sun, Feb 22, 2015 at 10:46 PM, Andy t3k...@gmail.com wrote:
On 02/22/2015 01:21 PM, shalu jhanwar wrote:
Hi guys,
thanks a lot for all
Hi guys,
I am using SVM and Random forest classifiers from scikit learn. I wonder is
it possible to plot the decision boundary of the model on my own training
dataset so that I can have a feeling of the data? Is there any in-built
example available in Scikit which I can refer to view let's say
On Feb 20, 2015, at 8:29 AM, shalu jhanwar shalu.jhanwa...@gmail.com
wrote:
Hi guys,
I am using SVM and Random forest classifiers from scikit learn. I wonder
is it possible to plot the decision boundary of the model on my own
training dataset so that I can have a feeling of the data
Generally I do PCA and can plot the reduced dimension of the data (PC1 and
PC2). Here I'm interested in knowing the boundary decision of the
classifier.
S.
On Fri, Feb 20, 2015 at 6:34 PM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Fri, Feb 20, 2015 at 05:27:12PM +0100, shalu
, 2015 at 4:01 PM, shalu jhanwar shalu.jhanwa...@gmail.com
wrote:
Hi Scikit fans,
I am facing following error while performing classification with *single
feature* only:
reg = linear_model.LogisticRegression()
*scores.append(reg.fit(X_train, y_train).score(X_test, y_test))*
Traceback (most
their values .
*From:* shalu jhanwar [mailto:shalu.jhanwa...@gmail.com]
*Sent:* Friday, October 24, 2014 11:36 AM
*To:* Pagliari, Roberto
*Subject:* Fwd: [Scikit-learn-general] Regarding TPR and FPR
Hey Roberto,
Could you please suggest something for my below query?
thanks!
S
Hi scikit users,
Can anyone let me know that how can i get mean TPR and mean FPR to plot ROC
using scikit?
I'm referring to http://scikit-learn.org/stable/auto_examples/plot_roc.html
link.
Any idea would be appreciated?
Thanks in advance.
Shalu
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