Diabetes | 天池糖尿病血糖预测比赛 精准医疗 初赛B榜24名 | CSV Processing library
kandi X-RAY | Diabetes Summary
kandi X-RAY | Diabetes Summary
先运行change.py增加特征维度，再运行baseline.py 其中d_train_20180102.csv 有5642行 d_train_20180102_add.csv 有6642行，加了A榜的1000行 如果要看A榜的线上成绩，则把baseline.py里边的train test 和ol改一下路径即可.
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- Lazy train function
- Make train and test features .
- Change the contents of a table .
- Evaluate the mean squared error .
Diabetes Key Features
Diabetes Examples and Code Snippets
Community Discussions
Trending Discussions on Diabetes
QUESTION
I need to filter through a pandas dataframe, and sort one of the columns, returning the number of instances of each value in descending order. I've been able to accomplish this using a dictionary and some other things, but it isn't being returned in pandas format, which is what I need. Apparently, there is a built-in pandas functionality that can do this? What would that be?
This is the tsv that becomes the pandas dataframe:
...ANSWER
Answered 2022-Mar-31 at 19:47IIUC, use value_counts:
QUESTION
```
model2 = lm(1/glyhb~ gender + age + gender:age ,data = diabetes)
summary(model2)
```
Call:
lm(formula = 1/glyhb ~ gender + age + gender:age, data = diabetes)
Residuals:
Min 1Q Median 3Q Max
-0.149383 -0.019681 0.002455 0.029739 0.163164
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.2498158 0.0120415 20.746 < 2e-16 ***
genderfemale 0.0123141 0.0151608 0.812 0.417
age -0.0011384 0.0002363 -4.817 2.09e-06 ***
genderfemale:age -0.0002195 0.0003030 -0.724 0.469
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.04778 on 386 degrees of freedom
(因为不存在，13个观察量被删除了)
Multiple R-squared: 0.164, Adjusted R-squared: 0.1575
F-statistic: 25.24 on 3 and 386 DF, p-value: 6.264e-15
ANSWER
Answered 2022-Mar-29 at 22:29output:
pdf_document:
latex_engine: xelatex
QUESTION
I am doing a multiple linear regression with the following reproducible dataset (this is a small sample of my data):
...ANSWER
Answered 2022-Mar-27 at 07:31I would create a new column - see two options below.
(NB in lm() you don't have to specify SB_xlsx13$ each time you add a covariate if you list it as the data = argument once! This will make your output easier to read.)
Tidyverse approach: mutate and case_when:
QUESTION
df_nhpi %>%
select(AGE, SEX, MAR_STAT, HEIGHT, WEIGHT, BMI, HTN, HTNMED, MI, Smoking, COPD, CANCER, DIABETES) %>%
tbl_summary(by = SEX,
label = list(MAR_STAT ~ 'Marital Status',
HTN ~ 'Hypertension',
HTNMED ~ 'Hypertension Medication',
MI ~ 'Heart Attack',
Smoking ~ 'Smoking Status',
COPD ~ 'Chronic Obstructive Pulmonary Disease'),
type = list(c("HTN","HTNMED", "MI", "COPD", "CANCER") ~ "categorical"),
missing = "ifany",
missing_text = "Unknown",
statistic = list(all_continuous() ~ "{mean} ({sd})",
all_categorical() ~ "{n} ({p}%)"),
digits = all_continuous() ~ 2, percent = "column") %>%
add_stat_label() %>%
add_p(test = all_continuous() ~ "t.test", pvalue_fun =
function(x) style_pvalue(x, digits = 3)) %>%
bold_p() %>%
modify_caption("**Table 1. Baseline Characteristics**") %>% bold_labels()
ANSWER
Answered 2022-Mar-23 at 01:25I prepared two solutions that both report the proportion of missing data. Hopefully one of them works for you!
QUESTION
I try to make png from decision tree that i made before from a data. Using package pydotplus, I want to save the png in my local storage and show it. It work in google colab, but it error in jupyter. It said
GraphViz's executables not found
This is my code
...ANSWER
Answered 2022-Mar-14 at 14:20Hello Try these answers in the link, Maybe this is helpful. Or you can try importing OpenCV or PIL or matplotlib and write the variable as a png file. Install OpenCV library before doing this. You can do it by
QUESTION
In react native cli i was trying to login but not working nd same thing working fine in expo nd this error is showing please let me know what can i do to do this???? i have added the action ,reducer,component page
getting error this //
WARN Possible Unhandled Promise Rejection (id: 2): Error: [AsyncStorage] Passing null/undefined as value is not supported. If you want to remove value, Use .removeItem method instead. Passed value: undefined Passed key: userToken checkValidInput@http://localhost:8081/index.bundle?platform=android&dev=true&minify=false&app=com.easylab&modulesOnly=false&runModule=true:146791:24 http://localhost:8081/index.bundle?platform=android&dev=true&minify=false&app=com.easylab&modulesOnly=false&runModule=true:146835:24..........................
my action is like this // actions>index.js page
...ANSWER
Answered 2022-Feb-22 at 06:27Your problem is that you are trying to set userToken to null on this line:
QUESTION
I am working on Pima Indians Diabetes Database in Weka. I noticed that for decision tree J48 the tree is smaller as compared to the Random Tree. I am unable to understand why it is like this? Thank you.
...ANSWER
Answered 2022-Feb-21 at 19:57Though they both are decision trees, they employ different algorithms for constructing the tree, which will (most likely) give you a different outcome:
- J48 prunes the tree by default after it built its tree (Wikipedia).
- RandomTree (when using default parameters) inspects a maximum of
log2(num_attributes)attributes for generating splits.
QUESTION
I'm trying to update the number of neurons in each hidden layer for dynamically created layers. For example, the output as seen in the model.summary() shows each of the layers having either 5 or 10 Neurons, but not a 5 then 10 or 10 then 5 which is what I'd like.
...ANSWER
Answered 2022-Feb-11 at 08:30You could try defining n_layers as a list of lists:
QUESTION
I wanted to use the optimal k value to conduct kNN clasification and predict the dependent variable diabetes in test set using train set and compare the results with the real values.
I've already got optimal k value and got the accruacy already. After that, I wanted to compare the results with the real value with using confussionMatrix but I got the problem with the different length.
I've already checked that nrow and length quantities are same(with 74) but it still have same problem.
Could you help me to overcome this problem?
My codes are as like below
...ANSWER
Answered 2022-Feb-11 at 05:27I think you are looking to this:
QUESTION
I just wanted to conduct a kNN classification with the situation when k is 3. I would like to predict the dependent variable “diabetes” in valid set using train set and calculate the accuracy.
But I faced to the error message with
Error in knn(train = TrainXNormDF, test = ValidXNormDF, cl = MLdata2[, : 'train' and 'class' have different lengths
I can't solve this problem with get approach with
...ANSWER
Answered 2022-Feb-10 at 14:48Your cl variable is not the same length as your train variable. MLValidY only has 74 observations, while TrainXNormDF has 224.
cl should provide the true classification for every row in your training set.
Furthermore, cl is a data.frame instead of a vector.
Try the following:
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Install Diabetes
You can use Diabetes like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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