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# All possible combinations of n items selected randomly from a set of x items (algorithm)

By : Darren
Date : January 10 2021, 01:57 PM
wish help you to fix your issue Choosing p out of n items, this is the formula to tell you how many combinations there are.
code :

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## Algorithm - generating all combinations from items that must be chosen in sequence

By : user3782546
Date : March 29 2020, 07:55 AM
this one helps. It's a cartesian product, if exactly one item is chosen from each list/array, more precisely a list of the elements of the cartesian product. For lists, it's in Haskell's standard library:
code :
``````Prelude> sequence ["abc","def","ghi"]
,"bei","bfg","bfh","bfi","cdg","cdh","cdi","ceg","ceh","cei","cfg","cfh","cfi"]
``````

## algorithm to get all combinations of splitting up N items into K bins

By : user3810183
Date : March 29 2020, 07:55 AM
Hope that helps A common approach is as follows.
If you have, say, K bins, then add K-1 special values to your initial array. I will use the -1 value assuming that it never occurs in the initial array; you can choose a different value.
code :
``````[-1,1,2,3,4] -> {{}, {1,2,3,4}}
[2,1,3,-1,4] -> {{2,3,4}, {4}}
[3,1,2,-1,4] -> {{3,1,2}, {4}}
[1,3,-1,2,4] -> {{1,3}, {2,4}}
``````

## Efficient algorithm to get the combinations of all items in object

By : JEGAN
Date : March 29 2020, 07:55 AM
hope this fix your issue Your algorithm is almost O(2^n), you can discard a lot of combinations, but the num of elements will be (n! * (n-x)!) / x!.
To discard the useless combinations you can use an indexed array.
code :
`````` function combine(items, numSubItems) {
var result = [];
var indexes = new Array(numSubItems);
for (var i = 0 ; i < numSubItems; i++) {
indexes[i] = i;
}
while (indexes[0] < (items.length - numSubItems + 1)) {
var v = [];
for (var i = 0 ; i < numSubItems; i++) {
v.push(items[indexes[i]]);
}
result.push(v);
indexes[numSubItems - 1]++;
var l = numSubItems - 1; // reference always is the last position at beginning
while ( (indexes[numSubItems - 1] >= items.length) && (indexes[0] < items.length - numSubItems + 1)) {
l--; // the last position is reached
indexes[l]++;
for (var i = l +1 ; i < numSubItems; i++) {
indexes[i] = indexes[l] + (i - l);
}
}
}
return result;
}

var combinations = combine(["a", "b", "c", "d"], 3);
console.log(JSON.stringify(combinations));``````

## Optimum algorithm to check various combinations of items when number of items is too large

By : OlegMihaylov
Date : March 29 2020, 07:55 AM
hop of those help? The idea is to replace the computation of alpha with the so-called discrimination for each item from classical test theory (CTT). The discrimination is the correlation of the item score with a "true score" (which we would assume to be the row sum).
Let the data be
code :
``````dat <-  structure(list(CESD1 = c(1, 2, 2, 0, 1, 0, 0, 0, 0, 1), CESD2 = c(2, 3, 1, 0, 0, 1, 1, 1, 0, 1),
CESD3 = c(0, 3, 0, 1, 1, 0, 0, 0, 0, 0), CESD4 = c(1, 2, 0, 1, 0, 1, 1, 1, 0, 0),
CESD5 = c(0, 1, 0, 2, 1, 2, 2, 0, 0, 0), CESD6 = c(0, 3, 0, 1, 0, 0, 2, 0, 0, 0),
CESD7 = c(1, 2, 1, 1, 2, 0, 1, 0, 1, 0), CESD8 = c(1, 3, 1, 1, 0, 1, 0, 0, 1, 0),
CESD9 = c(0, 1, 0, 2, 0, 0, 1, 1, 0, 1), CESD10 = c(0, 1, 0, 2, 0, 0, 1, 1, 0, 1),
CESD11 = c(0, 2, 1, 1, 1, 1, 2, 3, 0, 0), CESD12 = c(0, 3, 1, 1, 1, 0, 2, 0, 0, 0),
CESD13 = c(0, 3, 0, 2, 1, 2, 1, 0, 1, 0), CESD14 = c(0, 3, 1, 2, 1, 1, 1, 0, 1, 1),
CESD15 = c(0, 2, 0, 1, 0, 1, 0, 1, 1, 0), CESD16 = c(0, 2, 2, 0, 0, 1, 1, 0, 0, 0),
CESD17 = c(0, 0, 0, 0, 0, 1, 1, 0, 0, 0), CESD18 = c(0, 2, 0, 0, 0, 0, 0, 0, 0, 1),
CESD19 = c(0, 3, 0, 0, 0, 0, 0, 1, 1, 0), CESD20 = c(0, 3, 0, 1, 0, 0, 0, 0, 0, 0)),
.Names = c("CESD1", "CESD2", "CESD3", "CESD4", "CESD5", "CESD6", "CESD7", "CESD8", "CESD9",
"CESD10", "CESD11", "CESD12", "CESD13", "CESD14", "CESD15", "CESD16", "CESD17",
"CESD18", "CESD19", "CESD20"), row.names = c(NA, -10L),
class = c("tbl_df", "tbl", "data.frame"))
``````
``````stat <- t(sapply(1:ncol(dat), function(ii){
dd <- dat[, ii]
# discrimination is the correlation of the item to the rowsum
disc <- if(var(dd, na.rm = TRUE) > 0) cor(dd, rowSums(dat[, -ii]), use = "pairwise")
# alpha that would be obtained when we skip this item
alpha <- psych::alpha(dat[, -ii])\$total\$raw_alpha
c(disc, alpha)
}))
dimnames(stat) <- list(colnames(dat), c("disc", "alpha^I"))
stat <- data.frame(stat)
``````
``````plot(stat, pch = 19)
``````
``````stat <- stat[order(stat\$disc), ]
this <- sapply(1:(nrow(stat)-2), function(ii){
ind <- match(rownames(stat)[1:ii], colnames(dat))
alpha <- psych::alpha(dat[, -ind, drop = FALSE])\$total\$raw_alpha
})

delete_these <- rownames(stat)[which(this > .9)]
psych::alpha(dat[, -match(delete_these, colnames(dat)), drop = FALSE])\$total\$raw_alpha
length(delete_these)
``````
``````stat <- stat[order(stat\$disc, decreasing = TRUE), ]
this <- sapply(1:(nrow(stat)-2), function(ii){
ind <- match(rownames(stat)[1:ii], colnames(dat))
alpha <- psych::alpha(dat[, -ind, drop = FALSE])\$total\$raw_alpha
})

delete_these <- rownames(stat)[which(this > .9)]
psych::alpha(dat[, -match(delete_these, colnames(dat)), drop = FALSE])\$total\$raw_alpha
length(delete_these)
``````

## After items selection in my ListView other items get randomly selected while scrolling Kotlin

By : user3196113
Date : March 29 2020, 07:55 AM
Hope this helps You don't appear to be changing the ListView's Cursor after you have made changes to/updated the underlying data.
Try, after making changes to the underlying data, updating the ListView's Cursor by
code :
``````public class MainActivity extends AppCompatActivity {

DBHelper dbhelper;
ListView myListView;
Cursor mCursor;

@Override
protected void onCreate(@Nullable Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
myListView = this.findViewById(R.id.myListView);
dbhelper = new DBHelper(this);
manageListView();
}

private void manageListView() {
mCursor = dbhelper.getAllRows();
@Override
public void onItemClick(AdapterView<?> parent, View view, int position, long id) {
manageListView();
}
});
} else {
}
}

for (int i=0; i < 10; i++) {
dbhelper.addRow("Apple", "Thing that falls from trees");
dbhelper.addRow("Cat", "Something that is furry and sits on mats");
dbhelper.addRow("Bear", "Something that is furry that eats honey but doesn't ssit on a mat");
dbhelper.addRow("Dog", "Something is furry and friendly");
dbhelper.addRow("Ferret", "Something that is furry and found up trouser legs");
dbhelper.addRow("Giraffe", "Something that has 5 legs one pointing up");
dbhelper.addRow("Hippo", "An animal that loves mud and water but not humans");
dbhelper.addRow("Ibis", "A white feathered flying thing");
dbhelper.addRow("Jaguar", "A car or a large black cat");
dbhelper.addRow("Kangaroo", "A marsupial that boxes, skips and has a puch for shopping trips");
dbhelper.addRow("Mammoth", "A big hairy elephant now extinct");
dbhelper.addRow("Nuthatch", "A small bird that does not customise nuts so they have hatches.");
dbhelper.addRow("Ostrich", "A l argefast running bird that does not fly");
dbhelper.addRow("Panther", "A skinny pink cat that walks on only two of it's four lehs");
dbhelper.addRow("Queen", "A female rule of a country");
dbhelper.addRow("Rhinocerous", "A Hippo like animal that has a name that is hard to spell");
dbhelper.addRow("Tiger", "A live verion of Winnie the Pooh's friend Tigger");
dbhelper.addRow("Stork", "A skinny ostrich that flies and delivers children through Dream World.");
}
}
}
``````
``````public class DBHelper extends SQLiteOpenHelper {

public DBHelper(@Nullable Context context) {
super(context, ContractClass.DBNAME,null,ContractClass.DBVERSION);
}

@Override
public void onCreate(SQLiteDatabase db) {
}

@Override
public void onUpgrade(SQLiteDatabase db, int oldVersion, int newVersion) {

}

public Cursor getAllRows() {
SQLiteDatabase db = this.getWritableDatabase();
}

SQLiteDatabase db = this.getWritableDatabase();
db.execSQL("UPDATE "
+ " SET " + ContractClass.FeedReaderContract.COLUMN_NAME_SELECTED
+ "= CASE " + ContractClass.FeedReaderContract.COLUMN_NAME_SELECTED +
" WHEN 1 THEN 0 ELSE 1 END " +
" WHERE " + ContractClass.FeedReaderContract.COLUMN_NAME_ENWORD + " LIKE ?",
new String[]{selected}
);
}

public long addRow(String enWord, String definition) {
SQLiteDatabase db = this.getWritableDatabase();
ContentValues cv = new ContentValues();
}
}
``````
``````public class MyCursorAdapter extends CursorAdapter {

public MyCursorAdapter(Context context, Cursor c) {
super(context, c, false);
}

@Override
public View newView(Context context, Cursor cursor, ViewGroup parent) {
return LayoutInflater.from(context).inflate(R.layout.row_list_row,parent,false);
}

@Override
public void bindView(View view, Context context, Cursor cursor) {
view.setBackgroundColor(0xFFF9F9F9);
} else {
view.setBackgroundColor(0xFFD9D9D9);
}
TextView tvBody = view.findViewById(R.id.txtName);
TextView tvPriority = view.findViewById(R.id.txtComment);
TextView tvPriority2 = view.findViewById(R.id.txtThird);
TextView tvPriority3 = view.findViewById(R.id.txtThi);